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Pipeline run

110f0408-1097-4622-ac43-eab9c352f1c2

Pipeline LLM cost (USD)
API 1: $0.0086 API 2: $0.0005 API 3: $0.0000 Total: $0.0091

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 pipeline development
Build and automate ETL pipelines and schedulers, using Python/Flask and AWS to ingest, transform, validate, and expose data from structured and unstructured sources. Also troubleshoot data issues, improve internal data processes, and support business teams with reliable data delivery.
"Create and manage ETL pipelines and job schedulers."
Tech stack maturity
Mainstream Modern
The skill set centers on widely used current technologies like AWS, Python, Flask, MySQL, and PostgreSQL, which fits a mainstream modern stack rather than a bleeding-edge or legacy one.
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 (22)
ETL Python Flask AWS MS SQL MySQL PostgreSQL Web Scraping Data Mining Data Processing Data Transformation Data Ingestion Data Validation Job Schedulers Cloud Infrastructure Open-Source Frameworks Open-Source Libraries Open-Source Tools Root Cause Analysis Metadata Management Dependency Management Workload Management
Skill cluster (7 dimension groups, role-scoped)
Relational Database Usage
MySQL PostgreSQL
Cloud Platforms
AWS
Data Lineage and Metadata
Metadata Management
Programming Languages for Data Work
Python
Site Troubleshooting and Debugging
Root Cause Analysis
Web Application Frameworks
Flask
Cross-cutting / unaligned
ETL MS SQL Web Scraping Data Mining Data Processing Data Transformation Data Ingestion Data Validation Job Schedulers Cloud Infrastructure Open-Source Frameworks Open-Source Libraries Open-Source Tools Dependency Management Workload Management
Show KRA description ↓
Create and manage ETL pipelines and job schedulers. Handle unstructured data and work to automate data ingestion and validation. Develop APIs with Flask and Python for data mining, transformation and ingestion to AWS. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Write clean, performant code to develop functional applications; build reusable code and libraries Collaborate with team to evaluate technologies we can leverage, including open-source frameworks, libraries, and tools. Support Business and application teams with respect to data-related requirements. Build proactive data validation automation to catch data integrity issues. Troubleshoot and resolve data issues using critical thinking. Minimum of 3 years of relevant data platform experience (structured/non-structured database, data extraction, data ingestion) A Degree discipline in Computer Science, Computer Information Systems, or other Engineering Disciplines. Experience in at least one of these databases: MS SQL, mySQL, PostGreSQL. Experience in AWS would be ideal and basic cloud infrastructure knowledge. Experience in Python is required for Web Scraping. Strong fundamentals in data mining & data processing methodologies Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Build processes supporting data transformation, data structures, metadata, dependency and workload management. Ability to thrive in challenging situations and solve complex problems Strong bias for action, and see yourself as an 'initiator' and 'problem solver' Analytical and problem-solving skills Customer centricity and Good communication

Signals

Skill full-stack-engineer
0.36
Alias
KRA data-engineer
0.62

Post-classification

Centroidupdated · n=249
Alias collision log
New-role queue
New skills captured14
New KRA captured

Captured for admin review

ETL primary Data Engineer pending
MS SQL primary Data Engineer pending
Web Scraping primary Data Engineer pending
Data Mining primary Data Engineer pending
Data Processing primary Data Engineer pending
Data Transformation primary Data Engineer pending
Data Ingestion primary Data Engineer pending
Data Validation primary Data Engineer pending
Job Schedulers primary Data Engineer pending
Cloud Infrastructure Data Engineer pending
Open-Source Frameworks Data Engineer pending
Open-Source Libraries Data Engineer pending
Open-Source Tools Data Engineer pending
Workload Management Data Engineer pending
Status: completed Created: 2026-05-27T15:03:37.195867Z Updated: 2026-06-12T16:56:39.406697Z API 3 duration: 59014 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

domain · Data Engineering & Analytics CASE DOMAIN

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

Domain=Data Engineering & Analytics; The JD centers on ETL pipelines, data ingestion/validation, APIs for data processing, AWS, Python, and data platform support, which best matches a Data Engineer role.

Matched skills

ETL pipelinesjob schedulersunstructured datadata ingestiondata validationFlaskPythonAWSMS SQLmySQLPostGreSQLweb scrapingdata miningdata processingroot cause analysis

Matched dimensions

Data Pipeline EngineeringData Ingestion and ValidationAPI Development for Data WorkflowsCloud Data Platform SupportProcess Automation and ScalabilityDatabase IntegrationData Troubleshooting and Root Cause Analysis

Matched KRAs

Create and manage ETL pipelines and job schedulersAutomate data ingestion and validationDevelop APIs with Flask and PythonIdentify, design, and implement internal process improvementsWrite clean, performant code to develop functional applicationsSupport Business and application teams with data-related requirementsBuild proactive data validation automationTroubleshoot and resolve data issues

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
1
Skipped

Job description

Day-to-Day Responsibilities
 Create and manage ETL pipelines and job schedulers. Handle unstructured data and work to automate data ingestion and validation. Develop APIs with Flask and Python for data mining, transformation and ingestion to AWS. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Write clean, performant code to develop functional applications; build reusable code and libraries Collaborate with team to evaluate technologies we can leverage, including open-source frameworks, libraries, and tools. Support Business and application teams with respect to data-related requirements. Build proactive data validation automation to catch data integrity issues. Troubleshoot and resolve data issues using critical thinking.
Required Qualifications
 Minimum of 3 years of relevant data platform experience (structured/non-structured database, data extraction, data ingestion) A Degree discipline in Computer Science, Computer Information Systems, or other Engineering Disciplines. Experience in at least one of these databases: MS SQL, mySQL, PostGreSQL. Experience in AWS would be ideal and basic cloud infrastructure knowledge. Experience in Python is required for Web Scraping. Strong fundamentals in data mining & data processing methodologies Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Build processes supporting data transformation, data structures, metadata, dependency and workload management.
Good To Have Critical Skills
 Ability to thrive in challenging situations and solve complex problems Strong bias for action, and see yourself as an 'initiator' and 'problem solver' Analytical and problem-solving skills Customer centricity and Good communication
(ref:hirist.com)

Skills from this JD

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

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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Python Primary 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)
Flask Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Flask id=1344 · flask

Aliases — catalog

  • Flask (CANONICAL) primary
  • flask 2 (VERSION)
  • flask 2.x (VERSION)
  • flask 3 (VERSION)
  • flask 3.x (VERSION)
  • flask2 (VERSION)
  • flask3 (VERSION)
  • flask>=3 (VERSION)

Context tags (catalog)

API Blueprints Flask-Migrate Flask-RESTful Flask-SQLAlchemy Flask-WTF JSON Jinja2 RESTful RESTful APIs SQLAlchemy Werkzeug debugging deployment gunicorn middleware routing session management template rendering unit testing virtual environments virtualenv

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Pallets Projects
License
bsd
Year introduced
2010
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Flask appears in many Python web developer job postings and remains a common lightweight framework in hiring pipelines, though often alongside Django/FastAPI rather than as a niche tool.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
35
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • 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
React Frontend Development
d_init_01
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)
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)
MS SQL 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
MySQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MySQL id=17 · mysql

Aliases — catalog

  • MySQL (CANONICAL) primary

Context tags (catalog)

ACID ACID compliance Backup Data Warehousing Database Design ER Diagrams EXPLAIN Indexes InnoDB JOIN Joins MyISAM Normalization PHPMyAdmin Query Optimization Replication SQL SQL queries Stored Procedures Transactions Triggers backup backup and restore backup strategies data modeling data normalization database design database normalization database schema foreign keys indexes indexing joins master-slave normalization performance tuning query optimization read replicas replication schema design schema management sharding stored procedures transaction isolation transaction management transactions triggers

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
Oracle Corporation
License
gpl_v2
Year introduced
1995
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: MySQL appears in a large share of backend/DB job descriptions and remains a standard managed offering across AWS RDS, Cloud SQL, and Azure Database, indicating broad hiring-pipeline 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)

  • Relational Data Modeling Catalog dimension db id 216

    Library dimension (catalog)

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

  • 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

  • Relational Database Usage Catalog dimension db id 371

    Library dimension (catalog)

    Roles linked in library: Go Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Data Modeling
relational-data-modeling
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)
Relational Database Usage
relational-database-usage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: PostgreSQL id=16 · postgresql

Aliases — catalog

  • PostgreSQL (CANONICAL) primary
  • PG 13 (VERSION)
  • PG 14 (VERSION)
  • PG 15 (VERSION)
  • PG 16 (VERSION)
  • PostgreSQL 13 (VERSION)
  • PostgreSQL 14 (VERSION)
  • PostgreSQL 15 (VERSION)
  • PostgreSQL 16 (VERSION)
  • Postgres 13 (VERSION)
  • Postgres 14 (VERSION)
  • Postgres 15 (VERSION)
  • Postgres 16 (VERSION)
  • pg10 (VERSION)
  • pg11 (VERSION)
  • pg12 (VERSION)
  • pg13 (VERSION)
  • pg14 (VERSION)
  • pg15 (VERSION)
  • pg16 (VERSION)
  • postgres (VERSION)
  • postgresql 10 (VERSION)
  • postgresql 11 (VERSION)
  • postgresql 12 (VERSION)
  • postgresql 13 (VERSION)
  • postgresql 14 (VERSION)
  • postgresql 15 (VERSION)
  • postgresql 16 (VERSION)
  • postgresql-16 (VERSION)
  • postgresql10 (VERSION)
  • postgresql11 (VERSION)
  • postgresql12 (VERSION)
  • postgresql13 (VERSION)
  • postgresql14 (VERSION)
  • postgresql15 (VERSION)
  • postgresql16 (VERSION)

Context tags (catalog)

ACID EXPLAIN JSONB PL/pgSQL PostGIS SQL VACUUM backup data integrity database migration extensions indexes indexing joins migration partitioning performance tuning pgAdmin query optimization replication schema stored procedures table partitioning transaction transactions triggers views

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
PostgreSQL Global Development Group
License
other_open
Year introduced
1996
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: PostgreSQL appears in a large share of backend/data engineering job postings and is a default managed option across AWS RDS, GCP Cloud SQL, and Azure Database, indicating broad hiring-pipeline adoption.

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)

  • Relational Data Modeling Catalog dimension db id 216

    Library dimension (catalog)

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

  • 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

  • Relational Database Usage Catalog dimension db id 371

    Library dimension (catalog)

    Roles linked in library: Go Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Data Modeling
relational-data-modeling
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)
Relational Database Usage
relational-database-usage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Scraping 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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Mining 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
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data 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 Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Transformation Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Data Transform id=1890 · data-transform

Aliases — catalog

  • Data Transform (CANONICAL) primary

Context tags (catalog)

ETL batch processing data aggregation data cleansing data integration data lineage data mapping data modeling data pipeline data quality data visualization data wrangling real-time processing schema evolution transformation logic

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Transformation Concept
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Data transformation is a core ETL/ELT concept and appears broadly across job descriptions for analytics, data engineering, and BI roles; it’s a standard pipeline requirement rather than a niche tool.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1445
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Pages and Data Modeling Catalog dimension db id 254

    Library dimension (catalog)

    Roles linked in library: Pega Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Pages and Data Modeling
data-pages-and-data-modeling
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Data Ingestion 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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Validation 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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Job Schedulers 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
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cloud Infrastructure 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
Open-Source Frameworks 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
Web Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Open-Source Libraries 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
Libraries
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Open-Source Tools 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
DevOps Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Root Cause Analysis Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: root cause analysis id=2392 · root-cause-analysis

Aliases — catalog

  • root cause analysis (CANONICAL) primary
  • root-cause analysis (CANONICAL)

Context tags (catalog)

5 Whys Continuous improvement Corrective action Corrective actions Data analysis Defect analysis Defect tracking Failure mode effects analysis Fishbone diagram Kaizen Lean methodology Pareto analysis Preventive action Preventive measures Problem-solving Process mapping Quality control Root cause identification Statistical process control continuous improvement corrective actions data collection defect analysis failure mode effects analysis problem-solving process mapping quality management root cause identification systematic approach trend analysis

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Root Cause Analysis Methodology
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Root cause analysis is a standard incident/postmortem skill in SRE, ITIL, and quality roles; it appears broadly in job descriptions for operations, QA, and manufacturing, not as a niche tool.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3301
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Observability and Diagnostics Catalog dimension db id 287

    Library dimension (catalog)

    Roles linked in library: Go Backend Developer, Java Backend Developer, Python Backend Developer

  • Site Troubleshooting and Debugging Catalog dimension db id 353

    Library dimension (catalog)

    Roles linked in library: Drupal Dev

  • Sitecore Troubleshooting and Maintenance Catalog dimension db id 447

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Observability and Diagnostics
observability-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Site Troubleshooting and Debugging
site-troubleshooting-and-debugging
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sitecore Troubleshooting and Maintenance
sitecore-troubleshooting-and-maintenance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Metadata Management Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Metadata management id=137 · metadata-management

Aliases — catalog

  • Metadata management (CANONICAL) primary

Context tags (catalog)

business glossary cataloging controlled vocabulary data catalog data classification data dictionary data governance data lineage data quality data stewardship master data management metadata repository ontology schema registry taxonomy

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Metadata Management Methodology
Confidence
0.92
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in data/platform JDs: roles for data governance, MDM, and cataloging routinely list metadata management alongside tools like Collibra/Alation and cloud data catalogs.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
109
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Lineage and Metadata Catalog dimension db id 28

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
Dependency Management Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: dependency management id=2284 · dependency-management

Aliases — catalog

  • dependency management (CANONICAL) primary
  • Dependency management (CANONICAL)

Context tags (catalog)

Composer Gradle Maven Pipenv artifact repository build automation dependency graph dependency injection dependency resolution dependency tree lock files module bundler npm package management pip semantic versioning transitive dependencies versioning yarn

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Dependency Management Methodology
Confidence
0.83
Version strategy
NOT_APPLICABLE

Maturity reasoning: Dependency management is a standard requirement in JDs for Python/Node/Java/.NET roles, and major package ecosystems (npm, pip, Maven, NuGet) make it a routine hiring-pipeline skill rather than a niche specialty.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3294
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Build and Dependency Management Catalog dimension db id 286

    Library dimension (catalog)

    Roles linked in library: Java Backend Developer

  • Sitecore Architecture and Maintainability Catalog dimension db id 449

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Build and Dependency Management
build-and-dependency-management
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sitecore Architecture and Maintainability
sitecore-architecture-and-maintainability
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Workload Management 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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
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
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)
Flask in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Flask in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)
MySQL in_db
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MySQL in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MySQL in_db
Relational Database Usage
relational-database-usage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Database Usage
relational-database-usage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Transformation new
Data Pages and Data Modeling
data-pages-and-data-modeling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Root Cause Analysis in_db
Observability and Diagnostics
observability-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Root Cause Analysis in_db
Site Troubleshooting and Debugging
site-troubleshooting-and-debugging
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Root Cause Analysis in_db
Sitecore Troubleshooting and Maintenance
sitecore-troubleshooting-and-maintenance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Metadata Management in_db
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
Dependency Management in_db
Build and Dependency Management
build-and-dependency-management
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Dependency Management in_db
Sitecore Architecture and Maintainability
sitecore-architecture-and-maintainability
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed MS SQL | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Web Scraping | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Mining | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Processing | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Ingestion | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Validation | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Job Schedulers | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Cloud Infrastructure | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Open-Source Frameworks | type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Open-Source Libraries | type=Libraries subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Open-Source Tools | type=DevOps Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Workload Management | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
dimension_skill_link_proposed Data Transformation ↔ Data Pages and Data Modeling
nano JD Parser — gpt-4.1-nano click to toggle
ExperienceMinimum of 3 years of relevant data platform experience
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Computer Science (or related)",
      "raw": "A Degree discipline in Computer Science, Computer Information Systems, or other Engineering Disciplines.",
      "requirement": "required"
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  ],
  "experience": {
    "max": null,
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    "raw": "Minimum of 3 years of relevant data platform experience"
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  "job_locations": [],
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  "role_archetype": "Data",
  "roles_and_responsibilities": [
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      "bullet_count": 0,
      "heading": "Day-to-Day Responsibilities",
      "heading_was_present": true,
      "source_marker": {
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        "last_5_words": "data issues using critical thinking."
      },
      "text": "Create and manage ETL pipelines and job schedulers. Handle unstructured data and work to automate data ingestion and validation. Develop APIs with Flask and Python for data mining, transformation and ingestion to AWS. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Write clean, performant code to develop functional applications; build reusable code and libraries Collaborate with team to evaluate technologies we can leverage, including open-source frameworks, libraries, and tools. Support Business and application teams with respect to data-related requirements. Build proactive data validation automation to catch data integrity issues. Troubleshoot and resolve data issues using critical thinking.",
      "word_count": 139
    },
    {
      "bullet_count": 0,
      "heading": "Required Qualifications",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Minimum of 3 years of",
        "last_5_words": "dependency and workload management."
      },
      "text": "Minimum of 3 years of relevant data platform experience (structured/non-structured database, data extraction, data ingestion) A Degree discipline in Computer Science, Computer Information Systems, or other Engineering Disciplines. Experience in at least one of these databases: MS SQL, mySQL, PostGreSQL. Experience in AWS would be ideal and basic cloud infrastructure knowledge. Experience in Python is required for Web Scraping. Strong fundamentals in data mining \u0026 data processing methodologies Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
      "word_count": 139
    },
    {
      "bullet_count": 0,
      "heading": "Good To Have Critical Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Ability to thrive in challenging",
        "last_5_words": "centricity and Good communication"
      },
      "text": "Ability to thrive in challenging situations and solve complex problems Strong bias for action, and see yourself as an \u0027initiator\u0027 and \u0027problem solver\u0027 Analytical and problem-solving skills Customer centricity and Good communication",
      "word_count": 36
    }
  ],
  "urls": [
    {
      "type": "other",
      "url": "https://hirist.com"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Flask"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "MS SQL"
    },
    {
      "is_primary": true,
      "skill_name": "MySQL"
    },
    {
      "is_primary": true,
      "skill_name": "PostgreSQL"
    },
    {
      "is_primary": true,
      "skill_name": "Web Scraping"
    },
    {
      "is_primary": true,
      "skill_name": "Data Mining"
    },
    {
      "is_primary": true,
      "skill_name": "Data Processing"
    },
    {
      "is_primary": true,
      "skill_name": "Data Transformation"
    },
    {
      "is_primary": true,
      "skill_name": "Data Ingestion"
    },
    {
      "is_primary": true,
      "skill_name": "Data Validation"
    },
    {
      "is_primary": true,
      "skill_name": "Job Schedulers"
    },
    {
      "is_primary": false,
      "skill_name": "Cloud Infrastructure"
    },
    {
      "is_primary": false,
      "skill_name": "Open-Source Frameworks"
    },
    {
      "is_primary": false,
      "skill_name": "Open-Source Libraries"
    },
    {
      "is_primary": false,
      "skill_name": "Open-Source Tools"
    },
    {
      "is_primary": false,
      "skill_name": "Root Cause Analysis"
    },
    {
      "is_primary": false,
      "skill_name": "Metadata Management"
    },
    {
      "is_primary": false,
      "skill_name": "Dependency Management"
    },
    {
      "is_primary": false,
      "skill_name": "Workload Management"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
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  "rejected": false,
  "rejection_reason": null,
  "run_id": "110f0408-1097-4622-ac43-eab9c352f1c2",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
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            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
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          },
          {
            "kra_text": "Implements data quality validation rules, reconciliation checks, and anomaly detection to ensure data completeness, accuracy, and consistency.",
            "sentence": "Build proactive data validation automation to catch data integrity issues.",
            "similarity": 0.6165
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
            "similarity": 0.5935
          }
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        "matched_count": null,
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        "role_id": 2,
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        "total_count": null
      },
      {
        "display_name": "MLOps Engineer",
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          {
            "kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
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          },
          {
            "kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
            "sentence": "Create and manage ETL pipelines and job schedulers.",
            "similarity": 0.5504
          },
          {
            "kra_text": "Coordinates model promotion workflows across development, staging, and production environments including integration testing and data contract validation.",
            "sentence": "Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
            "similarity": 0.5468
          }
        ],
        "matched_count": null,
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        "role_id": 16,
        "score": 0.5515,
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        "total_count": null
      },
      {
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        "kra_matches": [
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            "kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
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            "similarity": 0.5742
          },
          {
            "kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
            "sentence": "Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
            "similarity": 0.5411
          },
          {
            "kra_text": "Builds and maintains CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or CircleCI to automate build, test, security scanning, and deployment workflows.",
            "sentence": "Create and manage ETL pipelines and job schedulers.",
            "similarity": 0.4772
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.5308,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": [
          {
            "kra_text": "data capture and validation logic",
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          },
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            "sentence": "Troubleshoot and resolve data issues using critical thinking.",
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          },
          {
            "kra_text": "Requirements analysis and process translation",
            "sentence": "Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
            "similarity": 0.4722
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 24,
        "score": 0.5095,
        "slug": "pega-developer",
        "total_count": null
      },
      {
        "display_name": "Scala Backend Developer",
        "kra_matches": [
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            "kra_text": "automated backend checks",
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          },
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            "sentence": "Support Business and application teams with respect to data-related requirements.",
            "similarity": 0.5134
          },
          {
            "kra_text": "backend workflow orchestration",
            "sentence": "Build processes supporting data transformation, data structures, metadata, dependency and workload management.",
            "similarity": 0.4893
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 87,
        "score": 0.5065,
        "slug": "scala-backend-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Fullstack Developer",
        "kra_matches": null,
        "matched_count": 5,
        "matched_skills": [
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        "matched_skills": [
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        "score": 0.3571,
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        "kra_matches": null,
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        "display_name": "Fullstack Developer",
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        "matched_count": 4,
        "matched_skills": [
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          "MySQL",
          "PostgreSQL",
          "Python"
        ],
        "role_id": 435,
        "score": 0.2857,
        "slug": "fullstack-developer",
        "total_count": 14
      },
      {
        "display_name": "Node.js Backend Developer",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "AWS",
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          "MySQL",
          "PostgreSQL"
        ],
        "role_id": 82,
        "score": 0.2857,
        "slug": "node-backend-developer",
        "total_count": 14
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.95,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.95,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Data Pipeline Engineering",
      "Data Ingestion and Validation",
      "API Development for Data Workflows",
      "Cloud Data Platform Support",
      "Process Automation and Scalability",
      "Database Integration",
      "Data Troubleshooting and Root Cause Analysis"
    ],
    "matched_kras": [
      "Create and manage ETL pipelines and job schedulers",
      "Automate data ingestion and validation",
      "Develop APIs with Flask and Python",
      "Identify, design, and implement internal process improvements",
      "Write clean, performant code to develop functional applications",
      "Support Business and application teams with data-related requirements",
      "Build proactive data validation automation",
      "Troubleshoot and resolve data issues"
    ],
    "matched_skills": [
      "ETL pipelines",
      "job schedulers",
      "unstructured data",
      "data ingestion",
      "data validation",
      "Flask",
      "Python",
      "AWS",
      "MS SQL",
      "mySQL",
      "PostGreSQL",
      "web scraping",
      "data mining",
      "data processing",
      "root cause analysis"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on ETL pipelines, data ingestion/validation, APIs for data processing, AWS, Python, and data platform support, which best matches a Data Engineer role.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 249,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 12359,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12361,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "MS SQL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12363,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Web Scraping",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12365,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Mining",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12367,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Processing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12368,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Transformation",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12369,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Ingestion",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12370,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Validation",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 12371,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Job Schedulers",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 12372,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Cloud Infrastructure",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 12373,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Open-Source Frameworks",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 12374,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Open-Source Libraries",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 12375,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Open-Source Tools",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 12376,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Workload Management",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
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": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
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        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1980,
      "existing_alias_text": "Flask",
      "input_term": "Flask",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Flask",
        "id": 1344,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "flask",
        "sub_category_id": 35,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 406,
      "existing_alias_text": "AWS",
      "input_term": "AWS",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "AWS",
        "id": 187,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aws",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 134,
      "existing_alias_text": "MySQL",
      "input_term": "MySQL",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "MySQL",
        "id": 17,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "mysql",
        "sub_category_id": 29,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 121,
      "existing_alias_text": "PostgreSQL",
      "input_term": "PostgreSQL",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "PostgreSQL",
        "id": 16,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "postgresql",
        "sub_category_id": 29,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2894,
      "existing_alias_text": "Data Transform",
      "input_term": "Data Transformation",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "data-transform",
        "sub_category_id": 1445,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 3688,
      "existing_alias_text": "root cause analysis",
      "input_term": "Root Cause Analysis",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "root cause analysis",
        "id": 2392,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "root-cause-analysis",
        "sub_category_id": 3301,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 341,
      "existing_alias_text": "Metadata management",
      "input_term": "Metadata Management",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "Metadata management",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "metadata-management",
        "sub_category_id": 109,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 3552,
      "existing_alias_text": "Dependency management",
      "input_term": "Dependency Management",
      "matched_canonical": {
        "category_id": 8,
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "dependency-management",
        "sub_category_id": 3294,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
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  ],
  "candidate_roles": [
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      "role_archetype": null,
      "slug": "cloud-security-engineer",
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      "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.",
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      "rationale": null,
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      "slug": "full-stack-engineer",
      "source": "db"
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      "rationale": null,
      "role_archetype": "Engineering",
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      "slug": "engineering-manager",
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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,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    },
    {
      "display_name": "ML Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "ml-engineer",
      "source": "db"
    },
    {
      "display_name": "MLOps Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "ml-ops-engineer",
      "source": "db"
    },
    {
      "display_name": "AR/VR Engineer",
      "id": 8,
      "rationale": null,
      "role_archetype": null,
      "slug": "ar-vr-engineer",
      "source": "db"
    },
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      "display_name": "Python Backend Developer",
      "id": 80,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "python-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Java Backend Developer",
      "id": 79,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "java-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": "PHP Backend Developer",
      "id": 86,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
      "source": "db"
    },
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
      "source": "db"
    },
    {
      "display_name": "DevOps Engineer",
      "id": 10,
      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
    {
      "display_name": "Go Backend Developer",
      "id": 81,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Kotlin Backend Developer",
      "id": 84,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
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      "display_name": "Scala Backend Developer",
      "id": 87,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
      "source": "db"
    },
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      "display_name": "AI Engineer",
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      "rationale": null,
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      "slug": "ai-engineer",
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      "display_name": "Cloud Architect",
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      "rationale": null,
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      "slug": "cloud-architect",
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      "display_name": "Ruby Backend Developer",
      "id": 85,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "Drupal Dev",
      "id": 228,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "drupal-dev",
      "source": "db"
    },
    {
      "display_name": "Sitecore Dev",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "sitecore-dev",
      "source": "db"
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  ],
  "chosen_role": {
    "display_name": "Data Engineer",
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    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on ETL pipelines, data ingestion/validation, APIs for data processing, AWS, Python, and data platform support, which best matches a Data Engineer role.",
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    "slug": "data-engineer",
    "source": "db"
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      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
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        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
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          "slug": "cloud-security-engineer",
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      ]
    },
    {
      "dimension": {
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        "source": "db"
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      "input_skill": "Python",
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      "roles_from_db": [
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          "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.",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
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        "source": "db"
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      "input_skill": "Python",
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      "roles_from_db": [
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          "display_name": "Engineering Manager",
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          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages and Scripting",
        "id": 59,
        "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.",
        "slug": "programming-languages-and-scripting",
        "source": "db"
      },
      "input_skill": "Python",
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      "roles_from_db": [
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          "display_name": "Cyber Security Engineer",
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          "rationale": null,
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
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    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for ML Systems",
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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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        "source": "db"
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      "input_skill": "Python",
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      "roles_from_db": [
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          "display_name": "ML Engineer",
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        "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
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        "source": "db"
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      "roles_from_db": [
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          "rationale": null,
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    },
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        "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
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        "source": "db"
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      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
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          "rationale": null,
          "role_archetype": "Engineering",
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      ]
    },
    {
      "dimension": {
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        "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"
      },
      "input_skill": "Flask",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Web Application Frameworks",
        "id": 2,
        "rationale": "Server frameworks and runtimes used to build HTTP services, controllers, middleware, and request pipelines. These frameworks shape how backend endpoints are structured and delivered.",
        "slug": "web-application-frameworks",
        "source": "db"
      },
      "input_skill": "Flask",
      "llm_role": null,
      "roles_from_db": [
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        },
        {
          "display_name": "Fullstack Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 435,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "fullstack-developer",
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        },
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-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": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "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",
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          "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",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
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          "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",
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          "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"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
          "id": 13,
          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "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"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "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",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Data Modeling",
        "id": 216,
        "rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
        "slug": "relational-data-modeling",
        "source": "db"
      },
      "input_skill": "MySQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
          "id": 435,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "fullstack-developer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Database Design",
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        "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"
      },
      "input_skill": "MySQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "Backend Developer",
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          "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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Database Usage",
        "id": 371,
        "rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
        "slug": "relational-database-usage",
        "source": "db"
      },
      "input_skill": "MySQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Data Modeling",
        "id": 216,
        "rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
        "slug": "relational-data-modeling",
        "source": "db"
      },
      "input_skill": "PostgreSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
          "id": 435,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "fullstack-developer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "PostgreSQL",
      "llm_role": null,
      "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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Database Usage",
        "id": 371,
        "rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
        "slug": "relational-database-usage",
        "source": "db"
      },
      "input_skill": "PostgreSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Data Pages and Data Modeling",
        "id": 254,
        "rationale": "Defines how Pega applications source, shape, and expose data for cases and UI components. This includes declarative data access, parameterized data pages, and the data objects used to support process execution.",
        "slug": "data-pages-and-data-modeling",
        "source": "db"
      },
      "input_skill": "Data Transformation",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Diagnostics",
        "id": 287,
        "rationale": "Instrumentation and troubleshooting practices used to understand Java service behavior in production and lower environments. This cluster covers logs, metrics, traces, correlation IDs, and root-cause analysis from service telemetry.",
        "slug": "observability-and-diagnostics",
        "source": "db"
      },
      "input_skill": "Root Cause Analysis",
      "llm_role": null,
      "roles_from_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": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Site Troubleshooting and Debugging",
        "id": 353,
        "rationale": "Diagnosing and fixing Drupal site defects across custom code, configuration, and runtime behavior. This is a coherent cluster because Drupal developers are expected to trace issues from symptoms back to modules, templates, or config.",
        "slug": "site-troubleshooting-and-debugging",
        "source": "db"
      },
      "input_skill": "Root Cause Analysis",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Drupal Dev",
          "id": 228,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "drupal-dev",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Sitecore Troubleshooting and Maintenance",
        "id": 447,
        "rationale": "Diagnosing defects, regressions, and maintainability issues across Sitecore code, configuration, and content behavior. This is a coherent cluster because the role is expected to stabilize the site experience over time.",
        "slug": "sitecore-troubleshooting-and-maintenance",
        "source": "db"
      },
      "input_skill": "Root Cause Analysis",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Sitecore Dev",
          "id": 233,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "sitecore-dev",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Data Lineage and Metadata",
        "id": 28,
        "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
        "slug": "data-lineage-and-metadata",
        "source": "db"
      },
      "input_skill": "Metadata Management",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Build and Dependency Management",
        "id": 286,
        "rationale": "Project build, packaging, and dependency resolution skills used to compile and assemble Java services. This cluster matters because backend delivery depends on reproducible builds and controlled library versions.",
        "slug": "build-and-dependency-management",
        "source": "db"
      },
      "input_skill": "Dependency Management",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Sitecore Architecture and Maintainability",
        "id": 449,
        "rationale": "Structural design choices for keeping Sitecore solutions understandable, extensible, and safe to evolve. This dimension covers solution boundaries, code organization, and maintainability tradeoffs specific to Sitecore implementations.",
        "slug": "sitecore-architecture-and-maintainability",
        "source": "db"
      },
      "input_skill": "Dependency Management",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Sitecore Dev",
          "id": 233,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "sitecore-dev",
          "source": "db"
        }
      ]
    }
  ],
  "input_final_skills": [
    "ETL",
    "Python",
    "Flask",
    "AWS",
    "MS SQL",
    "MySQL",
    "PostgreSQL",
    "Web Scraping",
    "Data Mining",
    "Data Processing",
    "Data Transformation",
    "Data Ingestion",
    "Data Validation",
    "Job Schedulers",
    "Cloud Infrastructure",
    "Open-Source Frameworks",
    "Open-Source Libraries",
    "Open-Source Tools",
    "Root Cause Analysis",
    "Metadata Management",
    "Dependency Management",
    "Workload Management"
  ],
  "input_llm_skills": [
    "ETL",
    "Python",
    "Flask",
    "AWS",
    "MS SQL",
    "MySQL",
    "PostgreSQL",
    "Web Scraping",
    "Data Mining",
    "Data Processing",
    "Data Transformation",
    "Data Ingestion",
    "Data Validation",
    "Job Schedulers",
    "Cloud Infrastructure",
    "Open-Source Frameworks",
    "Open-Source Libraries",
    "Open-Source Tools",
    "Root Cause Analysis",
    "Metadata Management",
    "Dependency Management",
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      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Job Schedulers",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "job-schedulers",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Cloud Infrastructure",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "cloud-infrastructure",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Open-Source Frameworks",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Web Frameworks",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "open-source-frameworks",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Open-Source Libraries",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Libraries",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "open-source-libraries",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Open-Source Tools",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "DevOps Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "open-source-tools",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "root cause analysis",
          "alias_type": "CANONICAL",
          "id": 3688,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "root-cause analysis",
          "alias_type": "CANONICAL",
          "id": 4634,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "root cause analysis",
        "id": 2392,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "root-cause-analysis",
        "sub_category_id": 3301,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Diagnostics",
            "id": 287,
            "rationale": "Instrumentation and troubleshooting practices used to understand Java service behavior in production and lower environments. This cluster covers logs, metrics, traces, correlation IDs, and root-cause analysis from service telemetry.",
            "slug": "observability-and-diagnostics",
            "source": "db"
          },
          "input_skill": "Root Cause Analysis",
          "llm_role": null,
          "roles_from_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": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Site Troubleshooting and Debugging",
            "id": 353,
            "rationale": "Diagnosing and fixing Drupal site defects across custom code, configuration, and runtime behavior. This is a coherent cluster because Drupal developers are expected to trace issues from symptoms back to modules, templates, or config.",
            "slug": "site-troubleshooting-and-debugging",
            "source": "db"
          },
          "input_skill": "Root Cause Analysis",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Drupal Dev",
              "id": 228,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "drupal-dev",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Sitecore Troubleshooting and Maintenance",
            "id": 447,
            "rationale": "Diagnosing defects, regressions, and maintainability issues across Sitecore code, configuration, and content behavior. This is a coherent cluster because the role is expected to stabilize the site experience over time.",
            "slug": "sitecore-troubleshooting-and-maintenance",
            "source": "db"
          },
          "input_skill": "Root Cause Analysis",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Sitecore Dev",
              "id": 233,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "sitecore-dev",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Root Cause Analysis",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Metadata management",
          "alias_type": "CANONICAL",
          "id": 341,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Metadata management",
        "id": 137,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "metadata-management",
        "sub_category_id": 109,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Data Lineage and Metadata",
            "id": 28,
            "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
            "slug": "data-lineage-and-metadata",
            "source": "db"
          },
          "input_skill": "Metadata Management",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Metadata Management",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "dependency management",
          "alias_type": "CANONICAL",
          "id": 5917,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Dependency management",
          "alias_type": "CANONICAL",
          "id": 3552,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "dependency management",
        "id": 2284,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "dependency-management",
        "sub_category_id": 3294,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Build and Dependency Management",
            "id": 286,
            "rationale": "Project build, packaging, and dependency resolution skills used to compile and assemble Java services. This cluster matters because backend delivery depends on reproducible builds and controlled library versions.",
            "slug": "build-and-dependency-management",
            "source": "db"
          },
          "input_skill": "Dependency Management",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Java Backend Developer",
              "id": 79,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "java-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Sitecore Architecture and Maintainability",
            "id": 449,
            "rationale": "Structural design choices for keeping Sitecore solutions understandable, extensible, and safe to evolve. This dimension covers solution boundaries, code organization, and maintainability tradeoffs specific to Sitecore implementations.",
            "slug": "sitecore-architecture-and-maintainability",
            "source": "db"
          },
          "input_skill": "Dependency Management",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Sitecore Dev",
              "id": 233,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "sitecore-dev",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Dependency Management",
      "matched_via": "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": "Workload Management",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "workload-management",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "ETL",
    "MS SQL",
    "Web Scraping",
    "Data Mining",
    "Data Processing",
    "Data Ingestion",
    "Data Validation",
    "Job Schedulers",
    "Cloud Infrastructure",
    "Open-Source Frameworks",
    "Open-Source Libraries",
    "Open-Source Tools",
    "Workload Management"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on ETL pipelines, data ingestion/validation, APIs for data processing, AWS, Python, and data platform support, which best matches a Data Engineer role.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Flask",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "MS SQL",
      "tag": "new"
    },
    {
      "skill": "MySQL",
      "tag": "in_db"
    },
    {
      "skill": "PostgreSQL",
      "tag": "in_db"
    },
    {
      "skill": "Web Scraping",
      "tag": "new"
    },
    {
      "skill": "Data Mining",
      "tag": "new"
    },
    {
      "skill": "Data Processing",
      "tag": "new"
    },
    {
      "skill": "Data Transformation",
      "tag": "in_db"
    },
    {
      "skill": "Data Ingestion",
      "tag": "new"
    },
    {
      "skill": "Data Validation",
      "tag": "new"
    },
    {
      "skill": "Job Schedulers",
      "tag": "new"
    },
    {
      "skill": "Cloud Infrastructure",
      "tag": "new"
    },
    {
      "skill": "Open-Source Frameworks",
      "tag": "new"
    },
    {
      "skill": "Open-Source Libraries",
      "tag": "new"
    },
    {
      "skill": "Open-Source Tools",
      "tag": "new"
    },
    {
      "skill": "Root Cause Analysis",
      "tag": "in_db"
    },
    {
      "skill": "Metadata Management",
      "tag": "in_db"
    },
    {
      "skill": "Dependency Management",
      "tag": "in_db"
    },
    {
      "skill": "Workload Management",
      "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 Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "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.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "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": "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": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "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": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "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.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "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": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "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": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "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.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "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": "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
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            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
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          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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        "input_skill": "PostgreSQL",
        "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": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 16,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Pages and Data Modeling",
          "id": 254,
          "rationale": "Defines how Pega applications source, shape, and expose data for cases and UI components. This includes declarative data access, parameterized data pages, and the data objects used to support process execution.",
          "slug": "data-pages-and-data-modeling",
          "source": "db"
        },
        "dimension_id": 254,
        "input_skill": "Data Transformation",
        "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": [
          {
            "display_name": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "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": "Observability and Diagnostics",
          "id": 287,
          "rationale": "Instrumentation and troubleshooting practices used to understand Java service behavior in production and lower environments. This cluster covers logs, metrics, traces, correlation IDs, and root-cause analysis from service telemetry.",
          "slug": "observability-and-diagnostics",
          "source": "db"
        },
        "dimension_id": 287,
        "input_skill": "Root Cause Analysis",
        "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": "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": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2392,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Site Troubleshooting and Debugging",
          "id": 353,
          "rationale": "Diagnosing and fixing Drupal site defects across custom code, configuration, and runtime behavior. This is a coherent cluster because Drupal developers are expected to trace issues from symptoms back to modules, templates, or config.",
          "slug": "site-troubleshooting-and-debugging",
          "source": "db"
        },
        "dimension_id": 353,
        "input_skill": "Root Cause Analysis",
        "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": "Drupal Dev",
            "id": 228,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "drupal-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2392,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Sitecore Troubleshooting and Maintenance",
          "id": 447,
          "rationale": "Diagnosing defects, regressions, and maintainability issues across Sitecore code, configuration, and content behavior. This is a coherent cluster because the role is expected to stabilize the site experience over time.",
          "slug": "sitecore-troubleshooting-and-maintenance",
          "source": "db"
        },
        "dimension_id": 447,
        "input_skill": "Root Cause Analysis",
        "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": "Sitecore Dev",
            "id": 233,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "sitecore-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2392,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Lineage and Metadata",
          "id": 28,
          "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
          "slug": "data-lineage-and-metadata",
          "source": "db"
        },
        "dimension_id": 28,
        "input_skill": "Metadata Management",
        "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": 137,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Build and Dependency Management",
          "id": 286,
          "rationale": "Project build, packaging, and dependency resolution skills used to compile and assemble Java services. This cluster matters because backend delivery depends on reproducible builds and controlled library versions.",
          "slug": "build-and-dependency-management",
          "source": "db"
        },
        "dimension_id": 286,
        "input_skill": "Dependency Management",
        "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": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2284,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Sitecore Architecture and Maintainability",
          "id": 449,
          "rationale": "Structural design choices for keeping Sitecore solutions understandable, extensible, and safe to evolve. This dimension covers solution boundaries, code organization, and maintainability tradeoffs specific to Sitecore implementations.",
          "slug": "sitecore-architecture-and-maintainability",
          "source": "db"
        },
        "dimension_id": 449,
        "input_skill": "Dependency Management",
        "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": "Sitecore Dev",
            "id": 233,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "sitecore-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2284,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 1
  },
  "planner_output": null,
  "run_id": "110f0408-1097-4622-ac43-eab9c352f1c2"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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