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Pipeline run

054d6e8a-9b87-48e6-9271-8cdaa6cc4156

Pipeline LLM cost (USD)
API 1: $0.0076 API 2: $0.0002 API 3: $0.0000 Total: $0.0077

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data transformation and modeling
Build and tune SQL/Python/PySpark data engineering workflows on AWS Glue/RDS/Aurora, with a strong focus on dimensional data modeling, debugging, and integrating 3rd-party SaaS data sources.
"“Experience in designing and building dimensional data models”"
Tech stack maturity
Mainstream Modern
The listed skills center on AWS, Python, RDS, and SQL, which are characteristic of cloud-based data engineering on a modern but widely adopted stack.
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 (11)
SQL Python PySpark Data Engineering Data Modeling AWS AWS Glue RDS Aurora R Scala
Skill cluster (3 dimension groups, role-scoped)
Programming Languages for Data Work
SQL Python Scala
Cloud Platforms
AWS RDS
Cross-cutting / unaligned
PySpark Data Engineering Data Modeling AWS Glue Aurora R
Show KRA description ↓
• Good hands-on experience with database: SQL. • Experience in high-level programming language for analysis (e.g Python, R, Scala) • 2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python • Strong understanding of data structures, software design principles and algorithms. • Experience in designing and building dimensional data models to improve accessibility, efficiency, and quality of data • Experience with Cloud Services: AWS, AWS Glue, SQL, RDS, Aurora. • Should have min 2+ Year of experience. • Preferable Client facing experience. • Leadership capabilities. • Strong logical and debugging skills. • Good reputed college • MUST have excellent English (verbal and written). • Engineering/B.Tech/B.E degree or related from premier institutes • Strong analytical skills - strong problem solving skills, communicates in a clear and succinct manner and effectively evaluates information / data to make decisions, anticipates obstacles and develops plans to resolve • Experience in the integration with and/or management of externally-hosted 3rd Party Software as a Service applications • High level of energy and enthusiasm, with ability to thrive in a rapidly changing environment.

Signals

Skill data-engineer
0.44
Alias
KRA data-engineer
0.43

Post-classification

Centroidupdated · n=117
Alias collision log
New-role queue
New skills captured5
New KRA captured

Captured for admin review

PySpark primary Data Engineer pending
Data Engineering primary Data Engineer pending
Data Modeling primary Data Engineer pending
AWS Glue primary Data Engineer pending
Aurora primary Data Engineer pending
Status: completed Created: 2026-05-27T14:03:59.594049Z Updated: 2026-05-27T14:05:29.186524Z API 3 duration: 29484 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 hands-on SQL, Python/Pyspark, cloud data services, and building dimensional data models, which best matches a Data Engineer role.

Matched skills

SQLPythonRScalaPysparkAWSAWS GlueRDSAuroradata structuressoftware design principlesalgorithms

Matched dimensions

Data EngineeringCloud Data ServicesDimensional Data ModelingData Analysis and ProgrammingProblem Solving and DebuggingClient-facing Communication

Matched KRAs

designing and building dimensional data modelsimprove accessibility, efficiency, and quality of dataintegration with and/or management of externally-hosted SaaS applicationscommunicates in a clear and succinct mannerdevelop plans to resolve

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
3
Skipped

Job description

Must Have:  • Good hands-on experience with  database: SQL . • Experience in high-level programming language for analysis (e.g Python, R, Scala)   • 2-5 years of experience in the industry and minimum 1.5years of experince in Data Engineering / Pyspark \ python • Strong understanding of data structures, software design principles and algorithms. • Experience in designing and building dimensional data models to improve accessibility, efficiency, and quality of data • Experience with Cloud Services: AWS, AWS Glue, SQL, RDS, Aurora. Skills & Qualifications:  •  Should have min 2+ Year of experience. • Preferable Client facing experience. • Leadership capabilities. • Strong logical and debugging skills. • Good reputed college • MUST have excellent English (verbal and written). Qualifications/Requirements:  • Engineering/B.Tech/B.E degree or related from premier institutes • Strong analytical skills - strong problem solving skills, communicates in a clear and succinct manner and effectively evaluates information / data to make decisions, anticipates obstacles and develops plans to resolve • Experience in the integration with and/or management of externally-hosted 3rd Party Software as a Service applications • High level of energy and enthusiasm, with ability to thrive in a rapidly changing environment.

Skills from this JD

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

SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
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

  • 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 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)
R Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: R id=194 · r

Aliases — catalog

  • R (VERSION)
  • R 3 (VERSION)
  • R 3.x (VERSION)
  • R 4 (VERSION)
  • R 4.0 (VERSION)
  • R 4.1 (VERSION)
  • R 4.2 (VERSION)
  • R 4.3 (VERSION)
  • R 4.4 (VERSION)
  • R 4.x (VERSION)

Context tags (catalog)

Bioconductor CRAN R Markdown Shiny Tidyverse caret data.table dplyr ggplot2 glm lme4 lubridate rstan tidyr tidyverse

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
R Core Team
License
gpl_v2
Year introduced
1993
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
R 4.x

Maturity reasoning: R appears in many data science, statistics, and analytics job postings, and CRAN remains active with broad package usage across academia and industry.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scala Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Scala id=102 · scala

Aliases — catalog

  • Scala (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PySpark Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

  • Apache Spark (CANONICAL)
  • apache spark 3 (VERSION)
  • spark (VERSION)
  • spark 3 (VERSION)
  • spark 3.x (VERSION)
  • spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Distributed Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.94
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1021
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Data Engineering 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 Modeling Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: domain modeling id=2379 · domain-modeling

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Application Architecture Patterns Catalog dimension db id 293

    Library dimension (catalog)

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

  • Service Architecture and Design Patterns Catalog dimension db id 18

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Service Architecture and Design Patterns
service-architecture-and-design-patterns
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
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

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)
AWS Glue 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
Cloud Platforms
Sub-category
Data Integration
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RDS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: RDS id=1211 · rds

Aliases — catalog

  • RDS (CANONICAL)

Context tags (catalog)

AWS Aurora MySQL PostgreSQL SQL Server backup and restore cloudformation database migration high availability multi-AZ parameter groups performance tuning read replicas scalability security groups

Stored enrichment (catalog DB)

Category
Service
Sub-category
Managed Relational Database Service
Vendor
Amazon Web Services
License
proprietary
Year introduced
2009
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS RDS is a standard managed database service and appears frequently in cloud/DevOps job descriptions alongside PostgreSQL/MySQL on AWS, indicating broad hiring-pipeline adoption.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
918
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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Aurora 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
PLATFORM
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
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
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 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)
R in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scala in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Scala in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PySpark new
ETL and ELT Tooling
etl-and-elt-tooling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Modeling new
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Modeling new
Service Architecture and Design Patterns
service-architecture-and-design-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
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)
RDS in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Data Engineering | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed AWS Glue | type=Cloud Platforms subtype=Data Integration nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Aurora | type=Databases subtype=general nature=PLATFORM lifespan=MULTI_YEAR
dimension_skill_link_proposed PySpark ↔ ETL and ELT Tooling
role_dimension_link_proposed Data Engineer ↔ ETL and ELT Tooling
dimension_skill_link_proposed Data Modeling ↔ Application Architecture Patterns
dimension_skill_link_proposed Data Modeling ↔ Service Architecture and Design Patterns
nano JD Parser — gpt-4.1-nano click to toggle
Experience2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Python",
    "Scala",
    "AWS",
    "Make",
    "Algorithms",
    "Data Structures",
    "RDS",
    "Cloud",
    "SQL",
    "Models",
    "debugging"
  ],
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Engineering (or related)",
      "raw": "Engineering/B.Tech/B.E degree or related from premier institutes",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 5,
    "min": 2,
    "raw": "2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python"
  },
  "job_locations": [],
  "role": null,
  "role_aliases": [],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 6,
      "heading": "Must Have",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Good hands-on experience with",
        "last_5_words": "AWS, AWS Glue, SQL, RDS, Aurora."
      },
      "text": "\u2022 Good hands-on experience with database: SQL.\n\u2022 Experience in high-level programming language for analysis (e.g Python, R, Scala)\n\u2022 2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python\n\u2022 Strong understanding of data structures, software design principles and algorithms.\n\u2022 Experience in designing and building dimensional data models to improve accessibility, efficiency, and quality of data\n\u2022 Experience with Cloud Services: AWS, AWS Glue, SQL, RDS, Aurora.",
      "word_count": 66
    },
    {
      "bullet_count": 6,
      "heading": "Skills \u0026 Qualifications",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Should have min 2+",
        "last_5_words": "English (verbal and written)."
      },
      "text": "\u2022 Should have min 2+ Year of experience.\n\u2022 Preferable Client facing experience.\n\u2022 Leadership capabilities.\n\u2022 Strong logical and debugging skills.\n\u2022 Good reputed college\n\u2022 MUST have excellent English (verbal and written).",
      "word_count": 36
    },
    {
      "bullet_count": 4,
      "heading": "Qualifications/Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Engineering/B.Tech/B.E degree or",
        "last_5_words": "thrive in a rapidly changing environment."
      },
      "text": "\u2022 Engineering/B.Tech/B.E degree or related from premier institutes\n\u2022 Strong analytical skills - strong problem solving skills, communicates in a clear and succinct manner and effectively evaluates information / data to make decisions, anticipates obstacles and develops plans to resolve\n\u2022 Experience in the integration with and/or management of externally-hosted 3rd Party Software as a Service applications\n\u2022 High level of energy and enthusiasm, with ability to thrive in a rapidly changing environment.",
      "word_count": 66
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
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      "is_primary": true,
      "skill_name": "SQL"
    },
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      "is_primary": false,
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      "is_primary": false,
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      "is_primary": true,
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    },
    {
      "is_primary": true,
      "skill_name": "AWS Glue"
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      "is_primary": true,
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  ],
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  "nano_parsed": {
    "JD_type": "pass",
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    "role_aliases": [],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
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        "bullet_count": 6,
        "heading": "Must Have",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Good hands-on experience with",
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        },
        "text": "\u2022 Good hands-on experience with database: SQL.\n\u2022 Experience in high-level programming language for analysis (e.g Python, R, Scala)\n\u2022 2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python\n\u2022 Strong understanding of data structures, software design principles and algorithms.\n\u2022 Experience in designing and building dimensional data models to improve accessibility, efficiency, and quality of data\n\u2022 Experience with Cloud Services: AWS, AWS Glue, SQL, RDS, Aurora.",
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        "bullet_count": 6,
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  "rejected": false,
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      {
        "display_name": "Fullstack Developer",
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          {
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      },
      {
        "display_name": "Backend Developer",
        "kra_matches": [
          {
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          },
          {
            "kra_text": "Investigates and resolves production incidents, API bugs, and service degradation through root cause analysis, hotfixes, and post-mortems.",
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        ],
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      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
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        ],
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      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "persistence and data modeling",
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          },
          {
            "kra_text": "persistence and data modeling",
            "sentence": "2-5 years of experience in the industry and minimum 1.5 years of experience in Data Engineering / Pyspark / python",
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          },
          {
            "kra_text": "persistence and data modeling",
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        ],
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    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
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        ],
        "role_id": 2,
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      {
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      {
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      "slug": "data-engineer",
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    "confidence": 0.96,
    "is_new_role": false,
    "llm2_fired": false,
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    "matched_dimensions": [
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      "Dimensional Data Modeling",
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      "Problem Solving and Debugging",
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    "matched_kras": [
      "designing and building dimensional data models",
      "improve accessibility, efficiency, and quality of data",
      "integration with and/or management of externally-hosted SaaS applications",
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      "develop plans to resolve"
    ],
    "matched_skills": [
      "SQL",
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      "R",
      "Scala",
      "Pyspark",
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    "new_role_display_name": null,
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    "queued": false,
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    "new_skills_attached": [
      {
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        "queue_id": 6650,
        "role_display_name": "Data Engineer",
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        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6651,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Engineering",
        "status": "pending"
      },
      {
        "is_primary": true,
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        "skill_name": "Data Modeling",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6653,
        "role_display_name": "Data Engineer",
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        "skill_name": "AWS Glue",
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      },
      {
        "is_primary": true,
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        "skill_name": "Aurora",
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  }
}
API 2 — extract-details
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      "alias_persisted": false,
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
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        "typical_lifespan": "EVERGREEN",
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      "matched_via": "alias"
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    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
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      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
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      "matched_via": "alias"
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      "existing_alias_text": "R",
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        "is_also_category": false,
        "is_extractable": true,
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        "typical_lifespan": "EVERGREEN",
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      "matched_via": "alias"
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    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
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      "existing_alias_text": "Scala",
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        "is_also_category": false,
        "is_extractable": true,
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      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
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      "existing_alias_text": "Apache Spark",
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      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
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      "matched_via": "embedding_alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
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      "existing_alias_text": "AWS",
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      "dimension": {
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          "role_archetype": "Engineering",
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          "role_archetype": "Engineering",
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    },
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        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
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        "source": "db"
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      "input_skill": "AWS",
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      "roles_from_db": [
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          "display_name": ".NET Backend Developer",
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          "rationale": null,
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        {
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          "rationale": null,
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          "slug": "cybersecurity-engineer",
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        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
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        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
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        {
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          "rationale": null,
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        },
        {
          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
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          "display_name": "Kotlin Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "ML Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        },
        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
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        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
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          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
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        {
          "display_name": "Scala Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
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    {
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        "difficulty_hint": "well_known",
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        "id": 211,
        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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        "source": "db"
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      "input_skill": "AWS",
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      "roles_from_db": [
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          "display_name": "AI Engineer",
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          "slug": "ai-engineer",
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    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
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        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
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        "source": "db"
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      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
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          "rationale": null,
          "role_archetype": null,
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          "display_name": "Cloud Security Engineer",
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          "rationale": null,
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          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
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        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Posture Tools",
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        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Cloud Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "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": "RDS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
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        {
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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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          "slug": "cybersecurity-engineer",
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        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
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        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
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      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "domain modeling",
          "alias_type": "CANONICAL",
          "id": 3675,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Domain Modeling",
          "alias_type": "CANONICAL",
          "id": 5644,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "domain modeling",
        "id": 2379,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "domain-modeling",
        "sub_category_id": 2831,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Application Architecture Patterns",
            "id": 293,
            "rationale": "Structural patterns for organizing Python backend code into maintainable modules, layers, and feature boundaries. This is a coherent cluster because senior backend developers are expected to refactor and shape service internals over time.",
            "slug": "application-architecture-patterns",
            "source": "db"
          },
          "input_skill": "Data Modeling",
          "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": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Service Architecture and Design Patterns",
            "id": 18,
            "rationale": "Reusable backend design patterns used to structure service code and boundaries. Covers layering, dependency management, domain modeling, and maintainable service organization.",
            "slug": "service-architecture-and-design-patterns",
            "source": "db"
          },
          "input_skill": "Data Modeling",
          "llm_role": null,
          "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": "Java Backend Developer",
              "id": 79,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "java-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Kotlin Backend Developer",
              "id": 84,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "kotlin-server-backend-developer",
              "source": "db"
            },
            {
              "display_name": "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": "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"
            }
          ]
        }
      ],
      "input_skill": "Data Modeling",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "AWS",
          "alias_type": "CANONICAL",
          "id": 406,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "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"
      },
      "dimensions": [
        {
          "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",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            },
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Go Backend Developer",
              "id": 81,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "go-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Java Backend Developer",
              "id": 79,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "java-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Kotlin Backend Developer",
              "id": 84,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "kotlin-server-backend-developer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Scala Backend Developer",
              "id": 87,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "scala-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "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",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "AWS",
      "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": "AWS Glue",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "sub_category": "Data Integration",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "aws-glue",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "RDS",
          "alias_type": "CANONICAL",
          "id": 1847,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 11,
        "display_name": "RDS",
        "id": 1211,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "rds",
        "sub_category_id": 918,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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": "RDS",
          "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": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            },
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Go Backend Developer",
              "id": 81,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "go-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Java Backend Developer",
              "id": 79,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "java-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Kotlin Backend Developer",
              "id": 84,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "kotlin-server-backend-developer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Scala Backend Developer",
              "id": 87,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "scala-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "RDS",
      "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": "Aurora",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Databases",
          "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": "aurora",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Data Engineering",
    "AWS Glue",
    "Aurora"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on hands-on SQL, Python/Pyspark, cloud data services, and building dimensional data models, which best matches a Data Engineer role.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "R",
      "tag": "in_db"
    },
    {
      "skill": "Scala",
      "tag": "in_db"
    },
    {
      "skill": "PySpark",
      "tag": "in_db"
    },
    {
      "skill": "Data Engineering",
      "tag": "new"
    },
    {
      "skill": "Data Modeling",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "AWS Glue",
      "tag": "new"
    },
    {
      "skill": "RDS",
      "tag": "in_db"
    },
    {
      "skill": "Aurora",
      "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": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "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": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "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": "SQL",
        "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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "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"
          },
          {
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        ],
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        "skipped_reason": null
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          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "slug": "cybersecurity-engineer",
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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.",
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        "roles_from_db": [
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            "slug": "data-engineer",
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        "skipped_reason": null
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      {
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          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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          "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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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
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            "role_archetype": null,
            "slug": "ar-vr-engineer",
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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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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
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        "roles_from_db": [
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        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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          "source": "db"
        },
        "dimension_id": 293,
        "input_skill": "Data Modeling",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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            "display_name": ".NET Backend Developer",
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            "role_archetype": "Engineering",
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            "source": "db"
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            "display_name": "Python Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
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        "skill_tag": "new",
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        "dimension_id": 18,
        "input_skill": "Data Modeling",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "rationale": null,
            "role_archetype": "Engineering",
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
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            "display_name": "Scala Backend Developer",
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            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
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          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "AWS",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
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            "display_name": ".NET Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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          },
          {
            "display_name": "Backend Developer",
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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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          },
          {
            "display_name": "Cyber Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
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          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
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            "rationale": null,
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            "slug": "devops-engineer",
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          },
          {
            "display_name": "Fullstack Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
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          {
            "display_name": "Go Backend Developer",
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            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
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            "role_archetype": "Engineering",
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          },
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            "display_name": "Kotlin Backend Developer",
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            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
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            "display_name": "ML Engineer",
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            "slug": "ml-engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
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          },
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            "display_name": "Node.js Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "AWS",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
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          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "AWS",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
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          },
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            "display_name": "Cloud Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
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        ],
        "skill_dimension_saved": true,
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        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
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          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "AWS",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
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          },
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
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        ],
        "skill_dimension_saved": true,
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        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
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          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
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          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "RDS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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          },
          {
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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.",
            "slug": "backend-engineer",
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          },
          {
            "display_name": "Cyber Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
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          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
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          },
          {
            "display_name": "Kotlin Backend Developer",
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            "slug": "ml-ops-engineer",
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          {
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            "slug": "python-backend-developer",
            "source": "db"
          },
          {
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            "slug": "scala-backend-developer",
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        ],
        "skill_dimension_saved": true,
        "skill_id": 1211,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
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    "skill_dimension_saved": 0,
    "skipped": 3
  },
  "planner_output": null,
  "run_id": "054d6e8a-9b87-48e6-9271-8cdaa6cc4156"
}

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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