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Pipeline run

cb2cfa56-e8b0-49d9-8358-4ac3c03d51e8

Pipeline LLM cost (USD)
API 1: $0.0052 API 2: $0.0006 API 3: $0.0000 Total: $0.0059

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data transformation and modeling
Build and maintain AWS/Oracle ETL and data warehouse solutions for financial/operational data, including SCD dimensional models, parallel processing, shell-scripted Informatica workflows, and runbook/SLA support. Turn business needs into technical designs and documentation across the SDLC.
"Strong experience with Data Modelling concepts and Modern data architecture including cloud technologies."
Tech stack maturity
Mainstream Legacy
The skill set centers on established enterprise data warehousing and ETL technologies like Informatica, Oracle Database, fact tables, and star schema, which are characteristic of mainstream legacy environments.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (39)
AWS Oracle Oracle ERP Oracle Database Slowly Changing Dimension Git Jira Agile Data Modeling ETL Unix Shell Scripting Informatica Data Warehousing Data Lake Star Schema Fact Tables Dimension Tables Aggregations Parallel Processing Kanban Informatica Intelligent Cloud Services Athena Apache Iceberg AWS Lambda Amazon EMR +14
Skill cluster (8 dimension groups, role-scoped)
Cloud Platforms
AWS AWS Lambda Azure
Programming Languages for Data Work
Python Scala Java
Data Modeling and Schema Design
Star Schema Fact Tables
BI and Visualization Tools
Tableau
ETL and ELT Tooling
Informatica
JavaScript and TypeScript
Node.js
Relational Database Design
Oracle Database
Cross-cutting / unaligned
Oracle Oracle ERP Slowly Changing Dimension Git Jira Agile Data Modeling ETL Unix Shell Scripting Data Warehousing Data Lake Dimension Tables Aggregations Parallel Processing Kanban Informatica Intelligent Cloud Services Athena Apache Iceberg Amazon EMR AWS Glue Databricks Oracle Cloud Infrastructure Alteryx IBM Planning Analytics TM1 Runbook SLA
Show KRA description ↓
• Senior Data Engineer must have prior hands-on experience developing and delivering data solution with AWS and/Or Oracle technologies. • Strong knowledge working with data from financial and operational systems, such as Oracle ERP Sales, Oracle DB and data modelling architecture with slow changing dimension (SCD). • Experience in running cloud platform with optimized solution architecture with the ability to meet the daily runbook SLA. • Strong experience with version control software like GIT and project management software like Jira with Agile/Kanban. • Strong experience with Data Modelling concepts and Modern data architecture including cloud technologies. • Ability to translate business requirements into technical requirements and deliveries. • Design and develop parallel processing ETL solutions for optimal resource usage and faster processing. • Understand ETL specification documents for mapping requirements and create mappings using transformations such as the Aggregator, Lookup, Router, Joiner, Union, Sorter, Normalizer and Update Strategy. • Create UNIX shell scripts as Informatica workflow wrapper and perform housekeeping activities like cleanup and archive files. • Experience in technical specification design - Proven experience in designing and building integrations supporting standard data modelling objects (Fact dimensions, aggregations, star schema, etc.) • Ability to provide end-to-end technical guidance on the software development life cycle (requirements through implementation). • Ability to create high quality solution design documentation for end-to-end solutions • Expertise in Data warehousing and modern data lake concepts. • 5+ years of experience in Data Engineering using tools such as:Informatica/IICS, Oracle DB and Oracle packages. AWS services. • Data platforms like Athena with iceberg, lambda, EMR, and glue, Data bricks. • Scripting languages like Python, Scala, Java or node. • 1+ years of experience in Unix shell scripting • 3+ years of experience working with Cloud like OCI, AWS, and Azure on Data technologies. • Experience with Publication and Education domain. • Prior experience or familiarity with Tableau/Alteryx. • Experience working with financial data like sales, revenue, cogs and manufacturing etc. • Experience with IBM planning Analytics (TM1).

Signals

Skill data-engineer
0.21
Alias data-engineer
1.00
KRA data-engineer
0.58

Post-classification

Centroidupdated · n=492
Alias collision log
New-role queue
New skills captured24
New KRA captured

Captured for admin review

Oracle primary Data Engineer pending
Oracle ERP primary Data Engineer pending
Slowly Changing Dimension primary Data Engineer pending
Jira primary Data Engineer pending
Kanban Data Engineer pending
Data Modeling primary Data Engineer pending
ETL primary Data Engineer pending
Unix Shell Scripting primary Data Engineer pending
Informatica Intelligent Cloud Services Data Engineer pending
Data Warehousing primary Data Engineer pending
Data Lake primary Data Engineer pending
Athena Data Engineer pending
Apache Iceberg Data Engineer pending
Amazon EMR Data Engineer pending
AWS Glue Data Engineer pending
Oracle Cloud Infrastructure Data Engineer pending
Alteryx Data Engineer pending
IBM Planning Analytics Data Engineer pending
TM1 Data Engineer pending
Dimension Tables primary Data Engineer pending
Aggregations primary Data Engineer pending
Parallel Processing primary Data Engineer pending
Runbook Data Engineer pending
SLA Data Engineer pending
Status: completed Created: 2026-05-27T17:17:05.640505Z Updated: 2026-05-27T17:19:15.315269Z API 3 duration: 27843 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

CASE A

slug: data-engineer · id: 2 · source: db

Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.21 does not contradict

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
11
Skipped

Job description

Overview

Build the Future

At McGraw Hill we create best-in-class, next-generation learning platforms that are used by millions of students and educators worldwide from kindergarten through graduate school. Our goal is to accelerate student success through intuitive and effective learning tools and content that maximize a teacher’s time and a student’s learning experience. Our engineering team drive progress and help build the future of learning. If you have the passion and technical expertise to thrive in an innovative and agile environment, we want to learn more about you.

What is this role about?

McGraw-Hill Education, the leading provider of digital and print educational materials is looking for a Senior Data Engineer for our Data Analytics Group.

The Senior Data Engineer in Data and Analytics is responsible for enhancing McGraw-Hill Education’s (MHE) business intelligence and data services capabilities, ensuring the delivery of actionable and timely insights to support financial, product, customer, user, and third-party data. This role also involves managing and monitoring the performance of the Data Platform, ensuring efficiency and reliability with hands-on data engineering, designing and architecting dynamic reporting, analytics, and modeling solutions to drive success in the education domain.

The ideal candidate will have a strong data engineering background, with expertise in Oracle Cloud Infrastructure (OCI) with Exadata, Informatica Intelligent Cloud Services (IICS) and/or Databricks, AWS, with tht advanced proficiency in SQL queries. Additionally, this role requires close collaboration with stakeholders to ensure the successful delivery of projects.

What you will be doing:

• Senior Data Engineer must have prior hands-on experience developing and delivering data solution with AWS and/Or Oracle technologies.
• Strong knowledge working with data from financial and operational systems, such as Oracle ERP Sales, Oracle DB and data modelling architecture with slow changing dimension (SCD). 
• Experience in running cloud platform with optimized solution architecture with the ability to meet the daily runbook SLA.
• Strong experience with version control software like GIT and project management software like Jira with Agile/Kanban.
• Strong experience with Data Modelling concepts and Modern data architecture including cloud technologies. 
• Ability to translate business requirements into technical requirements and deliveries.
• Design and develop parallel processing ETL solutions for optimal resource usage and faster processing.
• Understand ETL specification documents for mapping requirements and create mappings using transformations such as the Aggregator, Lookup, Router, Joiner, Union, Sorter, Normalizer and Update Strategy.
• Create UNIX shell scripts as Informatica workflow wrapper and perform housekeeping activities like cleanup and archive files.
• Experience in technical specification design - Proven experience in designing and building integrations supporting standard data modelling objects (Fact dimensions, aggregations, star schema, etc.)
• Ability to provide end-to-end technical guidance on the software development life cycle (requirements through implementation).
• Ability to create high quality solution design documentation for end-to-end solutions


What you need to be considered:

• Expertise in Data warehousing and modern data lake concepts.
• 5+ years of experience in Data Engineering using tools such as:Informatica/IICS, Oracle DB and Oracle packages. AWS services.
• Data platforms like Athena with iceberg, lambda, EMR, and glue, Data bricks.
• Scripting languages like Python, Scala, Java or node.
• 1+ years of experience in Unix shell scripting
• 3+ years of experience working with Cloud like OCI, AWS, and Azure on Data technologies.


Preferred:

• Experience with Publication and Education domain. 
• Prior experience or familiarity with Tableau/Alteryx. 
• Experience working with financial data like sales, revenue, cogs and manufacturing etc.
• Experience with IBM planning Analytics (TM1).


Why work for us?

At McGraw Hill, you will be empowered to make a real impact on a global scale. Every day your individual efforts contribute to the lives of millions. There has never been a better time to join McGraw Hill. In our culture of curiosity and innovation, you will be able to own your growth and develop as we do.

The work you do at McGraw Hill will be work those matters. We are collectively designing content that will build the future of education. Play your part and experience a sense of fulfilment that will inspire you to even greater heights.

If you are curious, open to new ideas and ready to make a difference, we want to talk to you.

We have a collective passion for the work we do and a curiosity to find new solutions. If you share our determination, together we will drive learning forward.

Here’s what we offer:

At McGraw Hill, you will be empowered to make a real impact on a global scale. Every day your individual efforts can contribute to the lives of millions.

McGraw Hill recruiters always use a “@mheducation.com” email address and/or from our Applicant Tracking System, iCIMS. Any variation of this email domain should be considered suspicious. Additionally, McGraw Hill recruiters and authorized representatives will never request sensitive information in email.

48831

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

AWS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS id=187 · aws

Aliases — catalog

  • AWS (CANONICAL) primary

Context tags (catalog)

API Gateway AWS CLI Auto Scaling CloudFormation CloudFront CloudTrail CloudWatch Cognito DynamoDB EC2 ECS EKS Elastic Beanstalk Elastic Load Balancing IAM KMS Lambda RDS Route 53 S3 SNS SQS Serverless VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Amazon
License
other_open
Year introduced
2006
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Oracle Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Oracle ERP Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Enterprise Resource Planning
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Oracle Database Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Oracle Database id=1566 · oracle-database

Aliases — catalog

  • Oracle Database (CANONICAL) primary

Context tags (catalog)

Backup and Recovery Data Guard Data Warehousing Indexing Oracle APEX Oracle Cloud Oracle Enterprise Manager Oracle Exadata Oracle Forms Oracle Fusion Middleware Oracle RAC Oracle SQL Oracle SQL*Plus PL/SQL Partitioning Performance Tuning RMAN SQL Developer

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
Oracle Corporation
License
proprietary
Year introduced
1979
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Oracle Database appears in many enterprise job postings and remains a standard RDBMS in large regulated environments; Oracle continues active vendor support and releases, indicating broad market demand.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
29
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Relational Database Design Catalog dimension db id 4

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Slowly Changing Dimension Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Slowly changing dimensions id=128 · slowly-changing-dimensions

Aliases — catalog

  • Slowly changing dimensions (CANONICAL) primary

Context tags (catalog)

ETL Kimball SCD Type 1 Type 2 Type 3 current flag data warehouse dimension table effective date end date fact table historization natural key surrogate key

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Data Warehouse Concept
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common data-warehouse concept in BI/ETL job descriptions and vendor docs (e.g., Kimball-style SCD patterns in Snowflake, BigQuery, and dbt ecosystems).

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
80
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Modeling and Schema Design Catalog dimension db id 26

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Modeling and Schema Design
data-modeling-and-schema-design
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Git Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Git id=1002 · git

Aliases — catalog

  • Git (CANONICAL)

Context tags (catalog)

CI/CD GitHub GitLab branching checkout clone commit fork merging pull request rebase remote repository stash versioning

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Version Control Tool
Vendor
Linus Torvalds
License
gpl_v2
Year introduced
2005
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Git is a hiring-pipeline staple: it appears in the vast majority of software engineering job descriptions and is the default VCS on GitHub/GitLab/Bitbucket.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
730
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Jira Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Project Management Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kanban Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Data Modeling Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: domain modeling id=2379 · domain-modeling

Aliases — catalog

  • domain modeling (CANONICAL) primary
  • Domain Modeling (CANONICAL)

Context tags (catalog)

CQRS DDD ERD UML aggregate bounded context business logic context map context mapping data modeling domain events domain-driven design entities entity event sourcing event storming microservices repositories repository pattern service layer services value object value objects

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Domain Modeling
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in software JDs under DDD/business analysis; many roles ask for domain modeling or domain-driven design, and it remains a standard design skill rather than a niche tool.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
2831
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Application Architecture Patterns Catalog dimension db id 293

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Python Backend Developer

  • Service Architecture and Design Patterns Catalog dimension db id 18

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Java Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Ruby Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Service Architecture and Design Patterns
service-architecture-and-design-patterns
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
ETL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Unix Shell Scripting Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Informatica Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Informatica id=117 · informatica

Aliases — catalog

  • Informatica (CANONICAL) primary

Context tags (catalog)

CDC Cloud Data Integration ELT ETL IICS PowerCenter data integration data quality data warehousing lookup transformation mapping repository session source qualifier workflow

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Integration Platform
Vendor
Informatica
License
proprietary
Year introduced
1993
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Informatica appears frequently in enterprise data-integration and ETL job postings, especially alongside cloud migration and MDM roles; it remains a common hiring keyword rather than a sunset technology.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
114
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension saved
Informatica Intelligent Cloud Services Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Integration Tools
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Warehousing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Data Lake Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Data Lakes id=1358 · data-lakes

Aliases — catalog

  • Data Lakes (CANONICAL)

Context tags (catalog)

AWS Lake Formation Azure Data Lake ETL big data data catalog data governance data ingestion data lakes vs data warehouses data modeling data pipelines data warehousing partitioning real-time analytics schema evolution serverless architecture

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Data Lake Architecture
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Data lakes are widely listed in cloud/data platform job descriptions and are a standard architecture in AWS, Azure, and GCP ecosystems; they’re a common hiring-pipeline staple rather than a niche pattern.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1025
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Athena Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Apache Iceberg Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
AWS Lambda Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS Lambda id=2295 · aws-lambda

Aliases — catalog

  • AWS Lambda (CANONICAL) primary

Context tags (catalog)

API Gateway AWS CLI AWS SAM AWS SDK CloudFormation DynamoDB IAM roles Java Lambda@Edge Node.js Python S3 Step Functions X-Ray containerization deployment event-driven microservices monitoring serverless step functions trigger triggers

Stored enrichment (catalog DB)

Category
Service
Sub-category
Serverless Function Service
Vendor
Amazon Web Services
License
other_open
Year introduced
2014
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Broadly listed in cloud/backend JDs and AWS’s serverless docs/marketplace; it’s a standard hiring-pipeline skill for event-driven apps and APIs.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
1704
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Cloud Platforms & Hosting Providers Catalog dimension db id 278

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer

  • Cloud Platforms & Services Catalog dimension db id 296

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Services
cloud-platforms-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Amazon EMR Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
AWS Glue Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Databricks Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Databricks id=1202 · databricks

Aliases — catalog

  • Databricks (CANONICAL)

Context tags (catalog)

Apache Spark Databricks Runtime Delta Lake MLflow SQL Analytics Spark cloud integration collaborative workspace data engineering data lakes data pipelines data visualization job scheduling machine learning notebooks real-time analytics

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Analytics Platform
Vendor
Databricks, Inc.
License
other_open
Year introduced
2013
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Databricks appears frequently in data engineering and analytics job postings, especially alongside Spark, Delta Lake, and lakehouse stacks; strong vendor adoption and broad enterprise usage signal mainstream demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
911
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scala Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Scala id=102 · scala

Aliases — catalog

  • Scala (CANONICAL) primary

Context tags (catalog)

Akka Apache Kafka Cats Flink JVM Monads Play Framework SBT ScalaTest Shapeless Spark Spark SQL ZIO case class for-comprehension functional programming implicit pattern matching typeclass

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
EPFL
License
apache_2
Year introduced
2004
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Scala still appears in many backend/data engineering JDs, especially with Spark and Akka, and remains supported by major JVM ecosystems; it’s not a sunset technology.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Java id=1 · java

Aliases — catalog

  • Java (CANONICAL) primary
  • JDK (VERSION)
  • JDK 10 (VERSION)
  • JDK 11 (VERSION)
  • JDK 12 (VERSION)
  • JDK 13 (VERSION)
  • JDK 14 (VERSION)
  • JDK 15 (VERSION)
  • JDK 16 (VERSION)
  • JDK 17 (VERSION)
  • JDK 18 (VERSION)
  • JDK 19 (VERSION)
  • JDK 20 (VERSION)
  • JDK 21 (VERSION)
  • JDK 5 (VERSION)
  • JDK 6 (VERSION)
  • JDK 7 (VERSION)
  • JDK 8 (VERSION)
  • JDK 9 (VERSION)
  • Java 1.0 (VERSION)
  • Java 1.1 (VERSION)
  • Java 1.2 (VERSION)
  • Java 1.3 (VERSION)
  • Java 1.4 (VERSION)
  • Java 1.5 (VERSION)
  • Java 1.6 (VERSION)
  • Java 1.7 (VERSION)
  • Java 1.8 (VERSION)
  • Java 10 (VERSION)
  • Java 11 (VERSION)
  • Java 12 (VERSION)
  • Java 13 (VERSION)
  • Java 14 (VERSION)
  • Java 15 (VERSION)
  • Java 16 (VERSION)
  • Java 17 (VERSION)
  • Java 18 (VERSION)
  • Java 19 (VERSION)
  • Java 20 (VERSION)
  • Java 21 (VERSION)
  • Java 5 (VERSION)
  • Java 6 (VERSION)
  • Java 7 (VERSION)
  • Java 8 (VERSION)
  • Java 9 (VERSION)
  • Java11 (VERSION)
  • Java17 (VERSION)
  • Java21 (VERSION)
  • Java8 (VERSION)
  • OpenJDK 11 (VERSION)
  • OpenJDK 17 (VERSION)
  • OpenJDK 21 (VERSION)
  • OpenJDK 8 (VERSION)
  • java 11 (VERSION)
  • java 17 (VERSION)
  • java 21 (VERSION)
  • java 4 (VERSION)
  • java 5 (VERSION)
  • java 6 (VERSION)
  • java 7 (VERSION)
  • java 8 (VERSION)
  • java lts (VERSION)
  • java-11 (VERSION)
  • java-17 (VERSION)
  • java-21 (VERSION)
  • java-4 (VERSION)
  • java-5 (VERSION)
  • java-6 (VERSION)
  • java-7 (VERSION)
  • java-8 (VERSION)
  • java11 (VERSION)
  • java17 (VERSION)
  • java21 (VERSION)
  • java4 (VERSION)
  • java5 (VERSION)
  • java6 (VERSION)
  • java7 (VERSION)
  • java8 (VERSION)
  • jdk 11 (VERSION)
  • jdk 17 (VERSION)
  • jdk 21 (VERSION)
  • jdk 4 (VERSION)
  • jdk 5 (VERSION)
  • jdk 6 (VERSION)
  • jdk 7 (VERSION)
  • jdk 8 (VERSION)
  • jdk11 (VERSION)
  • jdk17 (VERSION)
  • jdk21 (VERSION)
  • jdk4 (VERSION)
  • jdk5 (VERSION)
  • jdk6 (VERSION)
  • jdk7 (VERSION)
  • jdk8 (VERSION)
  • jvm21 (VERSION)

Context tags (catalog)

APIs Apache Tomcat Concurrency Design patterns Garbage collection GraalVM Gradle Hibernate JDBC JDK JPA JUnit JVM Java 8 Java EE JavaFX Kafka Lambda expressions Maven Microservices Mockito Object-oriented REST RESTful SOAP Servlets Spring Spring Boot Tomcat microservices

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Oracle
License
other_open
Year introduced
1995
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
21

Maturity reasoning: Java is a hiring-pipeline staple with very high JD volume across enterprise backend, Android, and cloud roles; it remains widely supported by major vendors and frameworks like Spring.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Java Language and JVM Catalog dimension db id 279

    Library dimension (catalog)

    Roles linked in library: Java Backend Developer, Kotlin Backend Developer, Scala Backend Developer

  • Kotlin and Java Catalog dimension db id 161

    Library dimension (catalog)

    Roles linked in library: Android Developer

  • Native Mobile Languages Catalog dimension db id 274

    Library dimension (catalog)

    Roles linked in library: Native Mobile Developer

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kotlin and Java
kotlin-and-java
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Native Mobile Languages
native-mobile-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Node.js Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Node.js id=1564 · node-js

Aliases — catalog

  • Node.js (CANONICAL) primary
  • Node 20 LTS (VERSION)
  • Node 20.x (VERSION)
  • Node.js 20 (VERSION)
  • Node.js 20 LTS (VERSION)
  • Node.js 20.x (VERSION)
  • node (VERSION)
  • node 10 (VERSION)
  • node 12 (VERSION)
  • node 14 (VERSION)
  • node 16 (VERSION)
  • node 18 (VERSION)
  • node 20 (VERSION)
  • node v10 (VERSION)
  • node v12 (VERSION)
  • node v14 (VERSION)
  • node v16 (VERSION)
  • node v18 (VERSION)
  • node v20 (VERSION)
  • node.js (VERSION)
  • node.js 10 (VERSION)
  • node.js 12 (VERSION)
  • node.js 14 (VERSION)
  • node.js 16 (VERSION)
  • node.js 18 (VERSION)
  • node.js 20 (VERSION)
  • nodejs (VERSION)
  • nodejs 10 (VERSION)
  • nodejs 12 (VERSION)
  • nodejs 14 (VERSION)
  • nodejs 16 (VERSION)
  • nodejs 18 (VERSION)
  • nodejs 20 (VERSION)

Context tags (catalog)

API Asynchronous Event-driven Express GraphQL JavaScript Jest Koa Microservices Middleware Mocha MongoDB Mongoose NestJS RESTful Socket.io TypeScript npm

Stored enrichment (catalog DB)

Category
Runtime
Sub-category
Javascript Runtime
Vendor
OpenJS Foundation
License
mit
Year introduced
2009
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
20

Maturity reasoning: Node.js appears in high-volume job postings across backend/full-stack roles and is a standard runtime in major cloud/vendor docs and ecosystem tooling, indicating broad hiring-pipeline adoption.

Skill profile (library / DB)

Skill nature
RUNTIME
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
67
Sub-category id
1872
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • JavaScript and TypeScript Catalog dimension db id 114

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, Ionic Developer, Node.js Backend Developer, React Frontend Developer, React Native Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Oracle Cloud Infrastructure Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Oracle Cloud id=1326 · oracle-cloud

Aliases — catalog

  • Oracle Cloud (CANONICAL) primary

Context tags (catalog)

APEX Autonomous Database Cloud Infrastructure Cloud Security Data Integration Exadata Identity and Access Management Kubernetes Microservices OCI Oracle Analytics Oracle Cloud Infrastructure Oracle Functions Serverless Terraform

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Oracle Corporation
License
proprietary
Year introduced
2016
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Oracle Cloud appears in enterprise job postings and vendor certifications, with OCI adoption driven by Oracle database workloads and cloud migration deals; it is a recognized major cloud platform, though less ubiquitous than AWS/Azure.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure id=188 · azure

Aliases — catalog

  • Azure (CANONICAL) primary

Context tags (catalog)

AKS ARM templates App Service Azure AD Azure Active Directory Azure App Service Azure Blob Azure Blob Storage Azure Cognitive Services Azure Cosmos DB Azure DevOps Azure DevTest Labs Azure Functions Azure Kubernetes Service Azure Logic Apps Azure Monitor Azure Networking Azure Resource Manager Azure SQL Azure SQL Database Azure Security Center Azure Storage Azure Storage Explorer Azure Virtual Machines Bicep Blob Storage Cloud Services Cosmos DB Entra ID Functions Infrastructure as Code Key Vault Log Analytics Logic Apps Resource Groups Serverless Computing Service Bus Storage Account Terraform Virtual Machines

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Microsoft
License
proprietary
Year introduced
2010
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Tableau Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Tableau id=150 · tableau

Aliases — catalog

  • Tableau (CANONICAL) primary

Context tags (catalog)

LOD expressions Tableau Cloud Tableau Desktop Tableau Prep Tableau Server actions calculated fields dashboards data blending data visualization extracts filters parameters published data sources workbooks

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Bi Analytics Platform
Vendor
Tableau Software
License
proprietary
Year introduced
2003
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform with strong vendor support and broad adoption.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
111
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • BI and Visualization Tools Catalog dimension db id 31

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
Alteryx Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Integration Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
IBM Planning Analytics Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Business Intelligence Tools
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
TM1 Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Business Intelligence Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Star Schema Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Star schema id=126 · star-schema

Aliases — catalog

  • Star schema (CANONICAL) primary

Context tags (catalog)

ETL Kimball OLAP aggregate table business intelligence conformed dimensions data mart denormalization dimension table fact table grain slowly changing dimension snowflake schema star join surrogate key

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Data Warehouse Architecture
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common data-warehouse pattern in BI/analytics JDs and vendor docs; widely used alongside Snowflake/BigQuery/Redshift for dimensional modeling, with no sunset or replacement signal.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
70
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Modeling and Schema Design Catalog dimension db id 26

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension saved
Fact Tables Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Fact tables id=127 · fact-tables

Aliases — catalog

  • Fact tables (CANONICAL) primary

Context tags (catalog)

ELT ETL Kimball OLAP aggregate tables conformed dimensions data mart data warehouse dimension tables grain partitioning slowly changing dimensions snowflake schema star schema surrogate key

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Data Warehouse Concept
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Core data-warehouse concept widely used in BI/analytics JDs and vendor docs (e.g., Snowflake, BigQuery, dbt) as a standard star-schema building block.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
80
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Modeling and Schema Design Catalog dimension db id 26

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension saved
Dimension Tables Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Warehousing
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Aggregations Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: aggregates id=3386 · aggregates

Aliases — catalog

  • aggregates (CANONICAL) primary

Context tags (catalog)

CQRS aggregate root bounded context business logic data integrity domain event domain-driven design entity event sourcing event-driven microservices repository pattern state management transactional consistency value object

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Ddd Aggregate
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: DDD aggregates are a standard concept in backend/domain modeling; they appear in many architecture JDs and are taught in mainstream DDD materials, with no successor replacing them.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2596
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Business Logic and Domain Modeling Catalog dimension db id 369

    Library dimension (catalog)

    Roles linked in library: Go Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Business Logic and Domain Modeling
business-logic-and-domain-modeling
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Parallel Processing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Runbook Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Runbooks id=408 · runbooks

Aliases — catalog

  • Runbooks (CANONICAL) primary
  • runbooks (CANONICAL)

Context tags (catalog)

ITIL SOP SRE automation best practices change management checklist deployment documentation escalation escalation matrix incident response knowledge base maintenance window monitoring on-call operational excellence operational procedures playbook postmortem process improvement process mapping rollback runbook as code runbook automation service desk service reliability service restoration standard operating procedure troubleshooting workflow

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Operational Procedure
Confidence
0.84
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common SRE/ops requirement in incident-response JDs and vendor docs (e.g., PagerDuty, Atlassian) for documented operational procedures; widely used across production teams.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
243
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Incident Response and Coordination Catalog dimension db id 74

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Observability and Operations Catalog dimension db id 143

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Operational Automation and Runbooks Catalog dimension db id 222

    Library dimension (catalog)

    Roles linked in library: MLOps Engineer

  • Release Documentation and Runbooks Catalog dimension db id 158

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Incident Response and Coordination
incident-response-and-coordination
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Observability and Operations
observability-and-operations
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Operational Automation and Runbooks
operational-automation-and-runbooks
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Release Documentation and Runbooks
release-documentation-and-runbooks
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
SLA Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Service Management
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
AWS in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
AWS in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Oracle Database in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Oracle Database in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Slowly Changing Dimension new
Data Modeling and Schema Design
data-modeling-and-schema-design
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Git in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Modeling new
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Modeling new
Service Architecture and Design Patterns
service-architecture-and-design-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Informatica in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension saved
Data Lake new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Lake new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
AWS Lambda in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
AWS Lambda in_db
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda in_db
Cloud Platforms & Services
cloud-platforms-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Databricks in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scala in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Scala in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Kotlin and Java
kotlin-and-java
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Native Mobile Languages
native-mobile-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Node.js in_db
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Node.js in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Oracle Cloud Infrastructure new
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Azure in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Tableau in_db
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
Star Schema in_db
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension saved
Fact Tables in_db
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension saved
Aggregations new
Business Logic and Domain Modeling
business-logic-and-domain-modeling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Runbook new
Incident Response and Coordination
incident-response-and-coordination
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Runbook new
Observability and Operations
observability-and-operations
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Runbook new
Operational Automation and Runbooks
operational-automation-and-runbooks
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Runbook new
Release Documentation and Runbooks
release-documentation-and-runbooks
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Oracle | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Oracle ERP | type=Enterprise Resource Planning subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Jira | type=Project Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Kanban | type=Practices subtype=general nature=PRACTICE lifespan=EVERGREEN
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Unix Shell Scripting | type=Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed Informatica Intelligent Cloud Services | type=Data Integration Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Data Warehousing | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Athena | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Apache Iceberg | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Amazon EMR | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed AWS Glue | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Alteryx | type=Data Integration Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed IBM Planning Analytics | type=Business Intelligence Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed TM1 | type=Business Intelligence Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Dimension Tables | type=Data Warehousing subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Parallel Processing | type=Data Engineering Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed SLA | type=Service Management subtype=general nature=CONCEPT lifespan=EVERGREEN
dimension_skill_link_proposed Slowly Changing Dimension ↔ Data Modeling and Schema Design
role_dimension_link_proposed Data Engineer ↔ Data Modeling and Schema Design
dimension_skill_link_proposed Data Modeling ↔ Application Architecture Patterns
dimension_skill_link_proposed Data Modeling ↔ Service Architecture and Design Patterns
dimension_skill_link_proposed Data Lake ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Data Lake ↔ React Frontend Development
dimension_skill_link_proposed Oracle Cloud Infrastructure ↔ Cloud Platforms for AI Deployment
dimension_skill_link_proposed Aggregations ↔ Business Logic and Domain Modeling
dimension_skill_link_proposed Runbook ↔ Incident Response and Coordination
dimension_skill_link_proposed Runbook ↔ Observability and Operations
dimension_skill_link_proposed Runbook ↔ Operational Automation and Runbooks
dimension_skill_link_proposed Runbook ↔ Release Documentation and Runbooks
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Data Engineer
CompanyMcGraw Hill
Experience5+ years of experience in Data Engineering
DomainEducation
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "At McGraw Hill we create",
      "last_5_words": "we want to learn more about you."
    },
    "text": "At McGraw Hill we create best-in-class, next-generation learning platforms that are used by millions of students and educators worldwide from kindergarten through graduate school. Our goal is to accelerate student success through intuitive and effective learning tools and content that maximize a teacher\u2019s time and a student\u2019s learning experience. Our engineering team drive progress and help build the future of learning. If you have the passion and technical expertise to thrive in an innovative and agile environment, we want to learn more about you.",
    "word_count": 84
  },
  "certifications": [],
  "company_name": "McGraw Hill",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "EdTech",
        "Learning Platforms"
      ],
      "domain": "Education"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 5,
    "raw": "5+ years of experience in Data Engineering"
  },
  "job_locations": [],
  "role": "Senior Data Engineer",
  "role_aliases": [
    "Data Engineer",
    "Senior Data Engineer",
    "Data Engineering Specialist"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 12,
      "heading": "What you will be doing",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Senior Data Engineer must have",
        "last_5_words": "end-to-end solution design documentation"
      },
      "text": "\u2022 Senior Data Engineer must have prior hands-on experience developing and delivering data solution with AWS and/Or Oracle technologies.\n\u2022 Strong knowledge working with data from financial and operational systems, such as Oracle ERP Sales, Oracle DB and data modelling architecture with slow changing dimension (SCD).\n\u2022 Experience in running cloud platform with optimized solution architecture with the ability to meet the daily runbook SLA.\n\u2022 Strong experience with version control software like GIT and project management software like Jira with Agile/Kanban.\n\u2022 Strong experience with Data Modelling concepts and Modern data architecture including cloud technologies.\n\u2022 Ability to translate business requirements into technical requirements and deliveries.\n\u2022 Design and develop parallel processing ETL solutions for optimal resource usage and faster processing.\n\u2022 Understand ETL specification documents for mapping requirements and create mappings using transformations such as the Aggregator, Lookup, Router, Joiner, Union, Sorter, Normalizer and Update Strategy.\n\u2022 Create UNIX shell scripts as Informatica workflow wrapper and perform housekeeping activities like cleanup and archive files.\n\u2022 Experience in technical specification design - Proven experience in designing and building integrations supporting standard data modelling objects (Fact dimensions, aggregations, star schema, etc.)\n\u2022 Ability to provide end-to-end technical guidance on the software development life cycle (requirements through implementation).\n\u2022 Ability to create high quality solution design documentation for end-to-end solutions",
      "word_count": 263
    },
    {
      "bullet_count": 6,
      "heading": "What you need to be considered",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Expertise in Data warehousing",
        "last_5_words": "with Cloud like OCI, AWS"
      },
      "text": "\u2022 Expertise in Data warehousing and modern data lake concepts.\n\u2022 5+ years of experience in Data Engineering using tools such as:Informatica/IICS, Oracle DB and Oracle packages. AWS services.\n\u2022 Data platforms like Athena with iceberg, lambda, EMR, and glue, Data bricks.\n\u2022 Scripting languages like Python, Scala, Java or node.\n\u2022 1+ years of experience in Unix shell scripting\n\u2022 3+ years of experience working with Cloud like OCI, AWS, and Azure on Data technologies.",
      "word_count": 66
    },
    {
      "bullet_count": 4,
      "heading": "Preferred",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Experience with Publication and",
        "last_5_words": "Analytics (TM1)."
      },
      "text": "\u2022 Experience with Publication and Education domain.\n\u2022 Prior experience or familiarity with Tableau/Alteryx.\n\u2022 Experience working with financial data like sales, revenue, cogs and manufacturing etc.\n\u2022 Experience with IBM planning Analytics (TM1).",
      "word_count": 48
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Oracle"
    },
    {
      "is_primary": true,
      "skill_name": "Oracle ERP"
    },
    {
      "is_primary": true,
      "skill_name": "Oracle Database"
    },
    {
      "is_primary": true,
      "skill_name": "Slowly Changing Dimension"
    },
    {
      "is_primary": true,
      "skill_name": "Git"
    },
    {
      "is_primary": true,
      "skill_name": "Jira"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    },
    {
      "is_primary": false,
      "skill_name": "Kanban"
    },
    {
      "is_primary": true,
      "skill_name": "Data Modeling"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "Unix Shell Scripting"
    },
    {
      "is_primary": true,
      "skill_name": "Informatica"
    },
    {
      "is_primary": false,
      "skill_name": "Informatica Intelligent Cloud Services"
    },
    {
      "is_primary": true,
      "skill_name": "Data Warehousing"
    },
    {
      "is_primary": true,
      "skill_name": "Data Lake"
    },
    {
      "is_primary": false,
      "skill_name": "Athena"
    },
    {
      "is_primary": false,
      "skill_name": "Apache Iceberg"
    },
    {
      "is_primary": false,
      "skill_name": "AWS Lambda"
    },
    {
      "is_primary": false,
      "skill_name": "Amazon EMR"
    },
    {
      "is_primary": false,
      "skill_name": "AWS Glue"
    },
    {
      "is_primary": false,
      "skill_name": "Databricks"
    },
    {
      "is_primary": false,
      "skill_name": "Python"
    },
    {
      "is_primary": false,
      "skill_name": "Scala"
    },
    {
      "is_primary": false,
      "skill_name": "Java"
    },
    {
      "is_primary": false,
      "skill_name": "Node.js"
    },
    {
      "is_primary": false,
      "skill_name": "Oracle Cloud Infrastructure"
    },
    {
      "is_primary": false,
      "skill_name": "Azure"
    },
    {
      "is_primary": false,
      "skill_name": "Tableau"
    },
    {
      "is_primary": false,
      "skill_name": "Alteryx"
    },
    {
      "is_primary": false,
      "skill_name": "IBM Planning Analytics"
    },
    {
      "is_primary": false,
      "skill_name": "TM1"
    },
    {
      "is_primary": true,
      "skill_name": "Star Schema"
    },
    {
      "is_primary": true,
      "skill_name": "Fact Tables"
    },
    {
      "is_primary": true,
      "skill_name": "Dimension Tables"
    },
    {
      "is_primary": true,
      "skill_name": "Aggregations"
    },
    {
      "is_primary": true,
      "skill_name": "Parallel Processing"
    },
    {
      "is_primary": false,
      "skill_name": "Runbook"
    },
    {
      "is_primary": false,
      "skill_name": "SLA"
    }
  ],
  "jd_role": {
    "display_name": "Senior Data Engineer",
    "rationale": null,
    "role_aliases": [
      "Data Engineer",
      "Senior Data Engineer",
      "Data Engineering Specialist"
    ],
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "At McGraw Hill we create",
        "last_5_words": "we want to learn more about you."
      },
      "text": "At McGraw Hill we create best-in-class, next-generation learning platforms that are used by millions of students and educators worldwide from kindergarten through graduate school. Our goal is to accelerate student success through intuitive and effective learning tools and content that maximize a teacher\u2019s time and a student\u2019s learning experience. Our engineering team drive progress and help build the future of learning. If you have the passion and technical expertise to thrive in an innovative and agile environment, we want to learn more about you.",
      "word_count": 84
    },
    "certifications": [],
    "company_name": "McGraw Hill",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "EdTech",
          "Learning Platforms"
        ],
        "domain": "Education"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": 5,
      "raw": "5+ years of experience in Data Engineering"
    },
    "job_locations": [],
    "role": "Senior Data Engineer",
    "role_aliases": [
      "Data Engineer",
      "Senior Data Engineer",
      "Data Engineering Specialist"
    ],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 12,
        "heading": "What you will be doing",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Senior Data Engineer must have",
          "last_5_words": "end-to-end solution design documentation"
        },
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}
API 2 — extract-details
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    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 272,
      "existing_alias_text": "Scala",
      "input_term": "Scala",
      "matched_canonical": {
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        "display_name": "Scala",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "scala",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1,
      "existing_alias_text": "Java",
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      "matched_canonical": {
        "category_id": 6,
        "display_name": "Java",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "java",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2500,
      "existing_alias_text": "Node.js",
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        "display_name": "Node.js",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "RUNTIME",
        "slug": "node-js",
        "sub_category_id": 1872,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 1962,
      "existing_alias_text": "Oracle Cloud",
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      "matched_via": "embedding_alias"
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      "alias_persisted": false,
      "existing_alias_id": 407,
      "existing_alias_text": "Azure",
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      "matched_via": "alias"
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      "alias_persisted": false,
      "existing_alias_id": 359,
      "existing_alias_text": "Tableau",
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        "display_name": "Tableau",
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        "typical_lifespan": "EVERGREEN",
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 330,
      "existing_alias_text": "Star schema",
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      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
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      "matched_via": "alias"
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      "alias_persisted": false,
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        "typical_lifespan": "EVERGREEN",
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      "matched_via": "alias"
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      "existing_alias_id": 4935,
      "existing_alias_text": "aggregates",
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        "is_also_category": false,
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        "skill_nature": "CONCEPT",
        "slug": "aggregates",
        "sub_category_id": 2596,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "embedding_alias"
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      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2460,
      "existing_alias_text": "Runbooks",
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        "category_id": 8,
        "display_name": "Runbooks",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "runbooks",
        "sub_category_id": 243,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "embedding_alias"
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      "slug": "cybersecurity-engineer",
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      "slug": "data-engineer",
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      "source": "db"
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      "display_name": "AI Engineer",
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    },
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    {
      "display_name": "Cloud Security Engineer",
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      "role_archetype": null,
      "slug": "cloud-security-engineer",
      "source": "db"
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    {
      "display_name": "Engineering Manager",
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      "rationale": null,
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      "slug": "engineering-manager",
      "source": "db"
    },
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      "display_name": "Ruby Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
    {
      "display_name": "PHP Backend Developer",
      "id": 86,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
      "source": "db"
    },
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      "display_name": "Web Developer",
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      "display_name": "Fullstack Developer",
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      "rationale": null,
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      "source": "db"
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      "slug": "ar-vr-engineer",
      "source": "db"
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      "rationale": null,
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      "slug": "android-engineer",
      "source": "db"
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      "display_name": "Native Mobile Developer",
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      "role_archetype": "Engineering",
      "slug": "native-mobile-developer",
      "source": "db"
    },
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      "display_name": "Pega Developer",
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      "role_archetype": "Engineering",
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      "source": "db"
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      "slug": "ionic-developer",
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      "rationale": null,
      "role_archetype": "Engineering",
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      "source": "db"
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "react-native-developer",
      "source": "db"
    },
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      "display_name": "Svelte Frontend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "svelte-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Vue Frontend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "vue-frontend-developer",
      "source": "db"
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  ],
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.21 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
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      "dimension": {
        "difficulty_hint": "well_known",
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        "source": "db"
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          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
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        {
          "display_name": "DevOps Engineer",
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          "slug": "devops-engineer",
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          "display_name": "Fullstack Developer",
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          "slug": "full-stack-engineer",
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          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        },
        {
          "display_name": "MLOps Engineer",
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          "role_archetype": null,
          "slug": "ml-ops-engineer",
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        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
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          "display_name": "Scala Backend Developer",
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          "slug": "cybersecurity-engineer",
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        "source": "db"
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      "input_skill": "AWS",
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    },
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        "source": "db"
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          "display_name": "Node.js Backend Developer",
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          "role_archetype": "Engineering",
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          "role_archetype": "Engineering",
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          "display_name": "Ruby Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "display_name": "Scala Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        "source": "db"
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        "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
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    {
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          "rationale": null,
          "role_archetype": null,
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    },
    {
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        "source": "db"
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          "rationale": null,
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        {
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          "rationale": null,
          "role_archetype": null,
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          "rationale": null,
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        {
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          "rationale": null,
          "role_archetype": null,
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          "role_archetype": null,
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          "role_archetype": "Engineering",
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        },
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "Scala Backend Developer",
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        "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
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        "source": "db"
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      "roles_from_db": [
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          "rationale": null,
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          "slug": "full-stack-engineer",
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          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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      ]
    },
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      "dimension": {
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        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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        "source": "db"
      },
      "input_skill": "Azure",
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          "display_name": "AI Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
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        "source": "db"
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      "input_skill": "Azure",
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      "roles_from_db": [
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "Cloud Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
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      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Cloud Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Vendor Product Families",
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        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
        "slug": "vendor-product-families",
        "source": "db"
      },
      "input_skill": "Azure",
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      "roles_from_db": [
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          "display_name": "Engineering Manager",
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          "rationale": null,
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          "slug": "engineering-manager",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
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      "input_skill": "Tableau",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
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        "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
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      "input_skill": "Star Schema",
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          "role_archetype": null,
          "slug": "data-engineer",
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        }
      ]
    },
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        "slug": "data-modeling-and-schema-design",
        "source": "db"
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      "input_skill": "Fact Tables",
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      "roles_from_db": [
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          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Implementing server-side business rules, domain entities, and service behavior in Go. This cluster is coherent because the role is judged on translating product requirements into maintainable domain logic rather than just wiring endpoints.",
        "slug": "business-logic-and-domain-modeling",
        "source": "db"
      },
      "input_skill": "Aggregations",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        "difficulty_hint": "well_known",
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        "rationale": "Processes and artifacts used to investigate, contain, and coordinate response to security events. This is a coherent cluster because the role must move from detection to containment, communication, and remediation tracking.",
        "slug": "incident-response-and-coordination",
        "source": "db"
      },
      "input_skill": "Runbook",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Cloud Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
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      "input_skill": "Runbook",
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      "roles_from_db": [
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          "display_name": "Cloud Architect",
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          "rationale": null,
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        "display_name": "Operational Automation and Runbooks",
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        "rationale": "Automation patterns, runbooks, and procedures used to keep model operations repeatable and recoverable. This cluster covers the day-to-day operational glue that turns release policy into executable steps.",
        "slug": "operational-automation-and-runbooks",
        "source": "db"
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      "input_skill": "Runbook",
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      "roles_from_db": [
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Operational documents that explain how to deploy, recover, and hand off systems safely. This is a coherent dimension because DevOps work depends on repeatable procedures and clear escalation paths.",
        "slug": "release-documentation-and-runbooks",
        "source": "db"
      },
      "input_skill": "Runbook",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
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      ]
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  "input_final_skills": [
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    "Oracle ERP",
    "Oracle Database",
    "Slowly Changing Dimension",
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    "Jira",
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    "Kanban",
    "Data Modeling",
    "ETL",
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              "id": 23,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-security-engineer",
              "source": "db"
            },
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Runbook",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Operational Automation and Runbooks",
            "id": 222,
            "rationale": "Automation patterns, runbooks, and procedures used to keep model operations repeatable and recoverable. This cluster covers the day-to-day operational glue that turns release policy into executable steps.",
            "slug": "operational-automation-and-runbooks",
            "source": "db"
          },
          "input_skill": "Runbook",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Release Documentation and Runbooks",
            "id": 158,
            "rationale": "Operational documents that explain how to deploy, recover, and hand off systems safely. This is a coherent dimension because DevOps work depends on repeatable procedures and clear escalation paths.",
            "slug": "release-documentation-and-runbooks",
            "source": "db"
          },
          "input_skill": "Runbook",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Runbook",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "SLA",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Service Management",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "UNVERSIONED",
          "volatility": "STABLE"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "sla",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Oracle",
    "Oracle ERP",
    "Jira",
    "Kanban",
    "ETL",
    "Unix Shell Scripting",
    "Informatica Intelligent Cloud Services",
    "Data Warehousing",
    "Athena",
    "Apache Iceberg",
    "Amazon EMR",
    "AWS Glue",
    "Alteryx",
    "IBM Planning Analytics",
    "TM1",
    "Dimension Tables",
    "Parallel Processing",
    "SLA"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.21 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Oracle",
      "tag": "new"
    },
    {
      "skill": "Oracle ERP",
      "tag": "new"
    },
    {
      "skill": "Oracle Database",
      "tag": "in_db"
    },
    {
      "skill": "Slowly Changing Dimension",
      "tag": "in_db"
    },
    {
      "skill": "Git",
      "tag": "in_db"
    },
    {
      "skill": "Jira",
      "tag": "new"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    },
    {
      "skill": "Kanban",
      "tag": "new"
    },
    {
      "skill": "Data Modeling",
      "tag": "in_db"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Unix Shell Scripting",
      "tag": "new"
    },
    {
      "skill": "Informatica",
      "tag": "in_db"
    },
    {
      "skill": "Informatica Intelligent Cloud Services",
      "tag": "new"
    },
    {
      "skill": "Data Warehousing",
      "tag": "new"
    },
    {
      "skill": "Data Lake",
      "tag": "in_db"
    },
    {
      "skill": "Athena",
      "tag": "new"
    },
    {
      "skill": "Apache Iceberg",
      "tag": "new"
    },
    {
      "skill": "AWS Lambda",
      "tag": "in_db"
    },
    {
      "skill": "Amazon EMR",
      "tag": "new"
    },
    {
      "skill": "AWS Glue",
      "tag": "new"
    },
    {
      "skill": "Databricks",
      "tag": "in_db"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Scala",
      "tag": "in_db"
    },
    {
      "skill": "Java",
      "tag": "in_db"
    },
    {
      "skill": "Node.js",
      "tag": "in_db"
    },
    {
      "skill": "Oracle Cloud Infrastructure",
      "tag": "in_db"
    },
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "Tableau",
      "tag": "in_db"
    },
    {
      "skill": "Alteryx",
      "tag": "new"
    },
    {
      "skill": "IBM Planning Analytics",
      "tag": "new"
    },
    {
      "skill": "TM1",
      "tag": "new"
    },
    {
      "skill": "Star Schema",
      "tag": "in_db"
    },
    {
      "skill": "Fact Tables",
      "tag": "in_db"
    },
    {
      "skill": "Dimension Tables",
      "tag": "new"
    },
    {
      "skill": "Aggregations",
      "tag": "in_db"
    },
    {
      "skill": "Parallel Processing",
      "tag": "new"
    },
    {
      "skill": "Runbook",
      "tag": "in_db"
    },
    {
      "skill": "SLA",
      "tag": "new"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Vendor Product Families",
          "id": 477,
          "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
          "slug": "vendor-product-families",
          "source": "db"
        },
        "dimension_id": 477,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Oracle Database",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1566,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Relational Database Design",
          "id": 4,
          "rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
          "slug": "relational-database-design",
          "source": "db"
        },
        "dimension_id": 4,
        "input_skill": "Oracle Database",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1566,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Modeling and Schema Design",
          "id": 26,
          "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
          "slug": "data-modeling-and-schema-design",
          "source": "db"
        },
        "dimension_id": 26,
        "input_skill": "Slowly Changing Dimension",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Git",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1002,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Software Concepts, Patterns \u0026 Practices",
          "id": 478,
          "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
          "slug": "software-concepts-patterns-practices",
          "source": "db"
        },
        "dimension_id": 478,
        "input_skill": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        },
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        "input_skill": "Data Modeling",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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          {
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      {
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        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
          {
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            "role_archetype": "Engineering",
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            "source": "db"
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            "role_archetype": "Engineering",
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            "source": "db"
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          {
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            "role_archetype": "Engineering",
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            "source": "db"
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            "slug": "scala-backend-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
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          "difficulty_hint": "well_known",
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          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
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        },
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        "input_skill": "Informatica",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
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        ],
        "skill_dimension_saved": true,
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        "skill_tag": "in_db",
        "skipped_reason": null
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      {
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          "display_name": "Cloud Storage and Data Services",
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          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
          "slug": "cloud-storage-and-data-services",
          "source": "db"
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        "input_skill": "Data Lake",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
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            "role_archetype": null,
            "slug": "cloud-architect",
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        ],
        "skill_dimension_saved": false,
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          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
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        },
        "dimension_id": 96,
        "input_skill": "Data Lake",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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      {
        "chosen_role_id": 2,
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          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "AWS Lambda",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
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            "role_archetype": "Engineering",
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          {
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            "slug": "backend-engineer",
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          {
            "display_name": "Cyber Security Engineer",
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            "rationale": null,
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            "slug": "cybersecurity-engineer",
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          {
            "display_name": "Data Engineer",
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            "rationale": null,
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            "slug": "data-engineer",
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          },
          {
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            "slug": "devops-engineer",
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          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
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          {
            "display_name": "Go Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
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          {
            "display_name": "Java Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
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          {
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          {
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            "rationale": null,
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            "slug": "ml-ops-engineer",
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          {
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            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": true,
        "skill_id": 2295,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
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        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms \u0026 Hosting Providers",
          "id": 278,
          "rationale": "Familiarity with vendor-specific hosting and backend services for deploying and scaling web applications.",
          "slug": "cloud-platforms-hosting-providers",
          "source": "db"
        },
        "dimension_id": 278,
        "input_skill": "AWS Lambda",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
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          {
            "display_name": "Scala Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
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          },
          {
            "display_name": "Web Developer",
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            "role_archetype": null,
            "slug": "web-developer",
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        ],
        "skill_dimension_saved": true,
        "skill_id": 2295,
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        "skipped_reason": null
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      {
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        "dimension": {
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          "source": "db"
        },
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
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            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
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        ],
        "skill_dimension_saved": true,
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      {
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          "rationale": "Deploying, configuring, and managing Python backends on major cloud and PaaS offerings.",
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        },
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "role_archetype": "Engineering",
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        "skill_dimension_saved": true,
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        "skipped_reason": null
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      {
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          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
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        },
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1202,
        "skill_tag": "in_db",
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      {
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          "source": "db"
        },
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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      },
      {
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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          {
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        ],
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        "skipped_reason": null
      },
      {
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
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          "source": "db"
        },
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        "roles_from_db": [
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            "display_name": "Cyber Security Engineer",
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            "role_archetype": null,
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      {
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          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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        "skill_tag": "in_db",
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        "roles_from_db": [
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        "roles_from_db": [
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        "roles_from_db": [
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Vendor Product Families",
          "id": 477,
          "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
          "slug": "vendor-product-families",
          "source": "db"
        },
        "dimension_id": 477,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "BI and Visualization Tools",
          "id": 31,
          "rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
          "slug": "bi-and-visualization-tools",
          "source": "db"
        },
        "dimension_id": 31,
        "input_skill": "Tableau",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 150,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Modeling and Schema Design",
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          "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
          "slug": "data-modeling-and-schema-design",
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        },
        "dimension_id": 26,
        "input_skill": "Star Schema",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
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            "display_name": "Data Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 126,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Modeling and Schema Design",
          "id": 26,
          "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
          "slug": "data-modeling-and-schema-design",
          "source": "db"
        },
        "dimension_id": 26,
        "input_skill": "Fact Tables",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
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            "display_name": "Data Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
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          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 127,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Business Logic and Domain Modeling",
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          "rationale": "Implementing server-side business rules, domain entities, and service behavior in Go. This cluster is coherent because the role is judged on translating product requirements into maintainable domain logic rather than just wiring endpoints.",
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          "source": "db"
        },
        "dimension_id": 369,
        "input_skill": "Aggregations",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Go Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
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        "chosen_role_id": 2,
        "dimension": {
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          "display_name": "Incident Response and Coordination",
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          "rationale": "Processes and artifacts used to investigate, contain, and coordinate response to security events. This is a coherent cluster because the role must move from detection to containment, communication, and remediation tracking.",
          "slug": "incident-response-and-coordination",
          "source": "db"
        },
        "dimension_id": 74,
        "input_skill": "Runbook",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Cloud Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
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            "display_name": "Cyber Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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      {
        "chosen_role_id": 2,
        "dimension": {
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          "display_name": "Observability and Operations",
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          "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
          "slug": "observability-and-operations",
          "source": "db"
        },
        "dimension_id": 143,
        "input_skill": "Runbook",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Cloud Architect",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Operational Automation and Runbooks",
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          "rationale": "Automation patterns, runbooks, and procedures used to keep model operations repeatable and recoverable. This cluster covers the day-to-day operational glue that turns release policy into executable steps.",
          "slug": "operational-automation-and-runbooks",
          "source": "db"
        },
        "dimension_id": 222,
        "input_skill": "Runbook",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "MLOps Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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        "dimension": {
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          "rationale": "Operational documents that explain how to deploy, recover, and hand off systems safely. This is a coherent dimension because DevOps work depends on repeatable procedures and clear escalation paths.",
          "slug": "release-documentation-and-runbooks",
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        },
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        "input_skill": "Runbook",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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    ],
    "new_skills_created": 0,
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    "skill_dimension_saved": 0,
    "skipped": 11
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  "run_id": "cb2cfa56-e8b0-49d9-8358-4ac3c03d51e8"
}