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Pipeline run

a8049623-3925-4c84-8855-013006afb2f6

Pipeline LLM cost (USD)
API 1: $0.0074 API 2: $0.0003 API 3: $0.0000 Total: $0.0077

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
SPARSE JD role baseline loaded sources · ai_index: role_baseline · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data pipeline development
Lead a data engineering team to build and improve AWS batch/streaming pipelines with PySpark, Spark, and Airflow, using Terraform/CI-CD and AWS services like S3, Glue, Lambda, and IAM. Also translate technical progress to business stakeholders and shape solutions for consumer needs.
"Solid background in AWS technologies and data pipeline build out for both batch and streaming"
Tech stack maturity
Modern Cloud Native
The stack centers on AWS-managed services, Infrastructure as Code with Terraform, CI/CD, and orchestration/data processing tools like Airflow and Spark, which are characteristic of a modern cloud-native data engineering environment.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.20 / 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 (15)
AWS Data Engineering PySpark Spark Airflow CI/CD Terraform Version Control Jira EC2 S3 IAM AWS Lambda AWS Glue SNS
Skill cluster (4 dimension groups, role-scoped)
Cloud Platforms
AWS S3 AWS Lambda
ETL and ELT Tooling
Spark
Infrastructure as Code
Terraform
Cross-cutting / unaligned
Data Engineering PySpark Airflow CI/CD Version Control Jira EC2 IAM AWS Glue SNS
Show KRA description ↓
• Hands on tech leader, managing and leading team of technical people by example • Solid background in AWS technologies and data pipeline build out for both batch and streaming • Communicate on technical aspects, translate and interact with business for updates and coordination • Collaborate and solution on consumer needs • Bring in innovation to overall solution delivery • Experience in Data Engineering with PySpark, Spark, Airflow • Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA • Knowledge of AWS stack - EC2, S3, IAM, Lambda, Glue, SNS, others

Signals

Skill ml-engineer
0.40
Alias data-engineer
1.00
KRA flutter-developer
0.53

Post-classification

Centroidupdated · n=426
Alias collision log
New-role queue
New skills captured7
New KRA capturedyes

Captured for admin review

Data Engineering primary Data Engineer pending
PySpark primary Data Engineer pending
Version Control primary Data Engineer pending
Jira primary Data Engineer pending
EC2 primary Data Engineer pending
AWS Glue primary Data Engineer pending
SNS primary Data Engineer pending
R&R fragment (sim 0.00) Data Engineer pending

• Hands on tech leader, managing and leading team of technical people by example • Solid background in AWS technologies and data pipeline build out for both batch and streaming • Communicate on techni…

Status: completed Created: 2026-05-27T16:22:32.893790Z Updated: 2026-05-27T16:24:37.886165Z API 3 duration: 49250 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 AWS-based data pipeline engineering, batch and streaming processing, and Spark/Airflow tooling, which best matches a Data Engineer role.

Matched skills

AWSPySparkSparkAirflowCI/CDTerraformversion control systemJIRAEC2S3IAMLambdaGlueSNS

Matched dimensions

Cloud Data EngineeringBatch and Streaming Data PipelinesData Platform DeliveryTechnical LeadershipBusiness and Stakeholder CommunicationInfrastructure as Code and CI/CD

Matched KRAs

managing and leading team of technical people by exampledata pipeline build out for both batch and streamingtranslate and interact with business for updates and coordinationcollaborate and solution on consumer needsbring in innovation to overall solution delivery

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

Hiring Sr AWS Data Engineer (Exp 4 to 14 Yrs). Interested candidates are requested to share your resume to Kheyali.m@tescra.com or apply to https://www.achnet.com/business/tescra/public/careers?jid=63d8b6ca463f164a9ef6c0b8

Job Location- Permanent Remote
Job Title-  Sr AWS Data Engineer
Experience: 4 to 14 Yrs
Job Responsibility-
• Hands on tech leader, managing and leading team of technical people by example
• Solid background in AWS technologies and data pipeline build out for both batch and streaming
• Communicate on technical aspects, translate and interact with business for updates and coordination
• Collaborate and solution on consumer needs
• Bring in innovation to overall solution delivery
Qualifications
• Experience in Data Engineering with PySpark, Spark, Airflow
• Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA
• Knowledge of AWS stack - EC2, S3, IAM, Lambda, Glue, SNS, others

Skills from this JD

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

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

Aliases — catalog

  • AWS (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

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

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

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

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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
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
Spark 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
Existing dimension (library) · Role↔dimension saved
Airflow Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Airflow id=265 · airflow

Aliases — catalog

  • Airflow (CANONICAL) primary
  • airflow 2 (VERSION)
  • airflow-2 (VERSION)
  • airflow2 (VERSION)
  • airflow2.x (VERSION)
  • apache airflow 2 (VERSION)

Context tags (catalog)

Apache Celery CeleryExecutor DAG ETL Executor Jinja templating Python SLA Sensors UI XCom backfill connections data pipeline executor hooks logging monitoring operators plugins scheduler task dependencies task instance variables

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Workflow Orchestration Tool
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2014
Confidence
0.95
Version strategy
SEPARATE_ENTITY
Version tag
2.x

Maturity reasoning: Apache Airflow appears in many data engineering job postings and is a common orchestration choice in production stacks; its GitHub activity and ecosystem remain strong, with no vendor sunset or clear replacement dominating JDs.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
130
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Workflow Orchestration for ML Pipelines Catalog dimension db id 54

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Workflow Orchestration for ML Pipelines
workflow-orchestration-for-ml-pipelines
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: CI/CD id=1190 · ci-cd

Aliases — catalog

  • CI/CD (CANONICAL)

Context tags (catalog)

Ansible CircleCI Docker GitLab CI Jenkins Kubernetes Terraform Travis CI automated testing build automation continuous deployment continuous integration deployment pipelines monitoring version control

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Ci Cd Process
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
900
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Terraform id=286 · terraform

Aliases — catalog

  • Terraform (CANONICAL) primary

Context tags (catalog)

AWS Azure GCP HCL IaC Terraform Cloud Terraform Enterprise Terraform Registry Terragrunt apply backend destroy infrastructure automation modules outputs plan providers provisioning remote backends remote state resource blocks resource management state file state management terraform apply terraform plan variables version control workspaces

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Infrastructure As Code Tool
Vendor
HashiCorp
License
mpl
Year introduced
2014
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Terraform is broadly listed in DevOps/SRE/cloud JDs and remains a standard IaC tool across AWS/Azure/GCP; HashiCorp’s ecosystem and widespread GitHub usage signal strong market adoption.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
191
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Infrastructure & Security Automation Frameworks Catalog dimension db id 249

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Infrastructure as Code Catalog dimension db id 132

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

  • Infrastructure as Code for ML Catalog dimension db id 57

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Infrastructure & Security Automation Frameworks
infrastructure-security-automation-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Infrastructure as Code for ML
infrastructure-as-code-for-ml
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Version Control 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
Development Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Jira Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Project Management Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
EC2 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
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
S3 Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: S3 id=1212 · s3

Aliases — catalog

  • S3 (CANONICAL)

Context tags (catalog)

AWS AWS CLI CORS CloudFormation IAM policies S3 Select bucket data lifecycle encryption event notifications multipart upload object storage static website hosting transfer acceleration versioning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Storage Platform
Vendor
Amazon
License
proprietary
Year introduced
2006
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Amazon S3 is a default cloud storage service in AWS job descriptions and architecture docs; it remains broadly adopted with no vendor sunset, and is commonly paired with S3-compatible storage rather than replaced.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
919
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

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Systems Programming Catalog dimension db id 166

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Systems Programming
d_init_02
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
IAM Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: IAM id=1217 · iam

Aliases — catalog

  • IAM (CANONICAL)

Context tags (catalog)

ABAC IAM governance MFA OAuth OpenID Connect RBAC SAML SSO access control audit logs directory services identity federation policy management security tokens user provisioning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Identity And Access Management Platform
Vendor
Amazon Web Services
License
proprietary
Year introduced
2011
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: IAM is a standard cloud/security platform skill; it appears routinely in AWS/Azure/GCP job descriptions and is a core control in vendor docs and compliance frameworks, indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
923
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS Lambda id=2295 · aws-lambda

Aliases — catalog

  • AWS Lambda (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

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

  • Cloud Platforms & Hosting Providers Catalog dimension db id 278

    Library dimension (catalog)

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

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

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

  • Cloud Platforms & Services Catalog dimension db id 296

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Services
cloud-platforms-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SNS 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
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
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)
PySpark new
ETL and ELT Tooling
etl-and-elt-tooling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Spark in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension saved
Airflow in_db
Workflow Orchestration for ML Pipelines
workflow-orchestration-for-ml-pipelines
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform in_db
Infrastructure & Security Automation Frameworks
infrastructure-security-automation-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform in_db
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform in_db
Infrastructure as Code for ML
infrastructure-as-code-for-ml
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
S3 in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
S3 in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
S3 in_db
Systems Programming
d_init_02
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
IAM in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
AWS Lambda in_db
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Lambda in_db
Cloud Platforms & Services
cloud-platforms-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

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 Version Control | type=Development Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Jira | type=Project Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed EC2 | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed AWS Glue | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed SNS | type=Cloud Platforms 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
nano JD Parser — gpt-4.1-nano click to toggle
RoleSr AWS Data Engineer
CompanyTescrA
Experience4 to 14 Yrs
DomainIT Services & Consulting
Location(remote)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": "TescrA",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": 14,
    "min": 4,
    "raw": "4 to 14 Yrs"
  },
  "job_locations": [
    {
      "aliases": [],
      "city": null,
      "country": null,
      "state": null,
      "work_mode": "remote"
    }
  ],
  "role": "Sr AWS Data Engineer",
  "role_aliases": [
    "AWS Data Engineer",
    "Data Engineer",
    "Cloud Data Engineer"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Job Responsibility",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Hands on tech leader, managing",
        "last_5_words": "innovation to overall solution delivery"
      },
      "text": "\u2022 Hands on tech leader, managing and leading team of technical people by example\n\u2022 Solid background in AWS technologies and data pipeline build out for both batch and streaming\n\u2022 Communicate on technical aspects, translate and interact with business for updates and coordination\n\u2022 Collaborate and solution on consumer needs\n\u2022 Bring in innovation to overall solution delivery",
      "word_count": 51
    },
    {
      "bullet_count": 3,
      "heading": "Qualifications",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Experience in Data Engineering with",
        "last_5_words": "S3, IAM, Lambda, Glue, SNS, others"
      },
      "text": "\u2022 Experience in Data Engineering with PySpark, Spark, Airflow\n\u2022 Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA\n\u2022 Knowledge of AWS stack - EC2, S3, IAM, Lambda, Glue, SNS, others",
      "word_count": 42
    }
  ],
  "urls": [
    {
      "type": "careers",
      "url": "https://www.achnet.com/business/tescra/public/careers?jid=63d8b6ca463f164a9ef6c0b8"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Data Engineering"
    },
    {
      "is_primary": true,
      "skill_name": "PySpark"
    },
    {
      "is_primary": true,
      "skill_name": "Spark"
    },
    {
      "is_primary": true,
      "skill_name": "Airflow"
    },
    {
      "is_primary": true,
      "skill_name": "CI/CD"
    },
    {
      "is_primary": true,
      "skill_name": "Terraform"
    },
    {
      "is_primary": true,
      "skill_name": "Version Control"
    },
    {
      "is_primary": true,
      "skill_name": "Jira"
    },
    {
      "is_primary": true,
      "skill_name": "EC2"
    },
    {
      "is_primary": true,
      "skill_name": "S3"
    },
    {
      "is_primary": true,
      "skill_name": "IAM"
    },
    {
      "is_primary": true,
      "skill_name": "AWS Lambda"
    },
    {
      "is_primary": true,
      "skill_name": "AWS Glue"
    },
    {
      "is_primary": true,
      "skill_name": "SNS"
    }
  ],
  "jd_role": {
    "display_name": "Sr AWS Data Engineer",
    "rationale": null,
    "role_aliases": [
      "AWS Data Engineer",
      "Data Engineer",
      "Cloud Data Engineer"
    ],
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": "TescrA",
    "ctc": null,
    "domain": {
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        "aliases": [],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": 14,
      "min": 4,
      "raw": "4 to 14 Yrs"
    },
    "job_locations": [
      {
        "aliases": [],
        "city": null,
        "country": null,
        "state": null,
        "work_mode": "remote"
      }
    ],
    "role": "Sr AWS Data Engineer",
    "role_aliases": [
      "AWS Data Engineer",
      "Data Engineer",
      "Cloud Data Engineer"
    ],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 5,
        "heading": "Job Responsibility",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Hands on tech leader, managing",
          "last_5_words": "innovation to overall solution delivery"
        },
        "text": "\u2022 Hands on tech leader, managing and leading team of technical people by example\n\u2022 Solid background in AWS technologies and data pipeline build out for both batch and streaming\n\u2022 Communicate on technical aspects, translate and interact with business for updates and coordination\n\u2022 Collaborate and solution on consumer needs\n\u2022 Bring in innovation to overall solution delivery",
        "word_count": 51
      },
      {
        "bullet_count": 3,
        "heading": "Qualifications",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Experience in Data Engineering with",
          "last_5_words": "S3, IAM, Lambda, Glue, SNS, others"
        },
        "text": "\u2022 Experience in Data Engineering with PySpark, Spark, Airflow\n\u2022 Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA\n\u2022 Knowledge of AWS stack - EC2, S3, IAM, Lambda, Glue, SNS, others",
        "word_count": 42
      }
    ],
    "urls": [
      {
        "type": "careers",
        "url": "https://www.achnet.com/business/tescra/public/careers?jid=63d8b6ca463f164a9ef6c0b8"
      }
    ]
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "a8049623-3925-4c84-8855-013006afb2f6",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
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        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 1.0,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Flutter Developer",
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          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Collaborate and solution on consumer needs",
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      },
      {
        "display_name": "DevOps Engineer",
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          {
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            "similarity": 0.609
          },
          {
            "kra_text": "Provisions and manages cloud infrastructure on AWS, Azure, or GCP using Terraform or CloudFormation to enforce infrastructure-as-code standards.",
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            "similarity": 0.4504
          },
          {
            "kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
            "sentence": "Bring in innovation to overall solution delivery",
            "similarity": 0.4429
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.5008,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
          {
            "kra_text": "Delivers features through CI/CD pipelines using automated tests, staged rollouts, feature flags, and incremental deployments.",
            "sentence": "Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA",
            "similarity": 0.5335
          },
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Communicate on technical aspects, translate and interact with business for updates and coordination",
            "similarity": 0.5075
          },
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Collaborate and solution on consumer needs",
            "similarity": 0.4446
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.4952,
        "slug": "full-stack-engineer",
        "total_count": null
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": [
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Communicate on technical aspects, translate and interact with business for updates and coordination",
            "similarity": 0.5223
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Bring in innovation to overall solution delivery",
            "similarity": 0.5136
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Collaborate and solution on consumer needs",
            "similarity": 0.4293
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 121,
        "score": 0.4884,
        "slug": "engineering-manager",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "kra_matches": [
          {
            "kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
            "sentence": "Communicate on technical aspects, translate and interact with business for updates and coordination",
            "similarity": 0.4973
          },
          {
            "kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
            "sentence": "Solid background in AWS technologies and data pipeline build out for both batch and streaming",
            "similarity": 0.4917
          },
          {
            "kra_text": "Architects blue-green, canary, and immutable infrastructure deployment patterns for zero-downtime releases and fast rollback capabilities.",
            "sentence": "Working knowledge with CI/CD tools, Infrastructure as code (Terraform or similar), Version control system, JIRA",
            "similarity": 0.4501
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 9,
        "score": 0.4797,
        "slug": "cloud-architect",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 6,
        "matched_skills": [
          "AWS",
          "AWS Lambda",
          "Airflow",
          "CI/CD",
          "S3",
          "Terraform"
        ],
        "role_id": 3,
        "score": 0.4,
        "slug": "ml-engineer",
        "total_count": 15
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": null,
        "matched_count": 5,
        "matched_skills": [
          "AWS",
          "AWS Lambda",
          "CI/CD",
          "S3",
          "Terraform"
        ],
        "role_id": 10,
        "score": 0.3333,
        "slug": "devops-engineer",
        "total_count": 15
      },
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "AWS",
          "AWS Lambda",
          "Apache Spark",
          "S3"
        ],
        "role_id": 2,
        "score": 0.2667,
        "slug": "data-engineer",
        "total_count": 15
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "AWS",
          "AWS Lambda",
          "Airflow",
          "S3"
        ],
        "role_id": 16,
        "score": 0.2667,
        "slug": "ml-ops-engineer",
        "total_count": 15
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "AWS",
          "AWS Lambda",
          "S3"
        ],
        "role_id": 5,
        "score": 0.2,
        "slug": "cybersecurity-engineer",
        "total_count": 15
      }
    ]
  },
  "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": 0.98,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.98,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Cloud Data Engineering",
      "Batch and Streaming Data Pipelines",
      "Data Platform Delivery",
      "Technical Leadership",
      "Business and Stakeholder Communication",
      "Infrastructure as Code and CI/CD"
    ],
    "matched_kras": [
      "managing and leading team of technical people by example",
      "data pipeline build out for both batch and streaming",
      "translate and interact with business for updates and coordination",
      "collaborate and solution on consumer needs",
      "bring in innovation to overall solution delivery"
    ],
    "matched_skills": [
      "AWS",
      "PySpark",
      "Spark",
      "Airflow",
      "CI/CD",
      "Terraform",
      "version control system",
      "JIRA",
      "EC2",
      "S3",
      "IAM",
      "Lambda",
      "Glue",
      "SNS"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on AWS-based data pipeline engineering, batch and streaming processing, and Spark/Airflow tooling, which best matches a Data Engineer role.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 426,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1469,
      "r_and_r_preview": "\u2022 Hands on tech leader, managing and leading team of technical people by example\n\u2022 Solid background in AWS technologies and data pipeline build out for both batch and streaming\n\u2022 Communicate on techni",
      "role_display_name": "Data Engineer",
      "role_slug": "data-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 19710,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Engineering",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19711,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "PySpark",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19712,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Version Control",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19713,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Jira",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19714,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "EC2",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19715,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "AWS Glue",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 19716,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "SNS",
        "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": 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": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2004,
      "existing_alias_text": "Apache Spark",
      "input_term": "PySpark",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Apache Spark",
        "id": 1350,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "apache-spark",
        "sub_category_id": 1021,
        "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": 2510,
      "existing_alias_text": "spark",
      "input_term": "Spark",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Apache Spark",
        "id": 1350,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "apache-spark",
        "sub_category_id": 1021,
        "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": 526,
      "existing_alias_text": "Airflow",
      "input_term": "Airflow",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Airflow",
        "id": 265,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "airflow",
        "sub_category_id": 130,
        "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": 1826,
      "existing_alias_text": "CI/CD",
      "input_term": "CI/CD",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "CI/CD",
        "id": 1190,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "ci-cd",
        "sub_category_id": 900,
        "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": 547,
      "existing_alias_text": "Terraform",
      "input_term": "Terraform",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Terraform",
        "id": 286,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "terraform",
        "sub_category_id": 191,
        "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": 1848,
      "existing_alias_text": "S3",
      "input_term": "S3",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "S3",
        "id": 1212,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "s3",
        "sub_category_id": 919,
        "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": 1853,
      "existing_alias_text": "IAM",
      "input_term": "IAM",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "IAM",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "iam",
        "sub_category_id": 923,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
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      "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": "sns",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Data Engineering",
    "Version Control",
    "Jira",
    "EC2",
    "AWS Glue",
    "SNS"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on AWS-based data pipeline engineering, batch and streaming processing, and Spark/Airflow tooling, which best matches a Data Engineer role.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Data Engineering",
      "tag": "new"
    },
    {
      "skill": "PySpark",
      "tag": "in_db"
    },
    {
      "skill": "Spark",
      "tag": "in_db"
    },
    {
      "skill": "Airflow",
      "tag": "in_db"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "Terraform",
      "tag": "in_db"
    },
    {
      "skill": "Version Control",
      "tag": "new"
    },
    {
      "skill": "Jira",
      "tag": "new"
    },
    {
      "skill": "EC2",
      "tag": "new"
    },
    {
      "skill": "S3",
      "tag": "in_db"
    },
    {
      "skill": "IAM",
      "tag": "in_db"
    },
    {
      "skill": "AWS Lambda",
      "tag": "in_db"
    },
    {
      "skill": "AWS Glue",
      "tag": "new"
    },
    {
      "skill": "SNS",
      "tag": "new"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Vendor Product Families",
          "id": 477,
          "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
          "slug": "vendor-product-families",
          "source": "db"
        },
        "dimension_id": 477,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "PySpark",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Spark",
        "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": 1350,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Workflow Orchestration for ML Pipelines",
          "id": 54,
          "rationale": "Workflow engines used to coordinate training, evaluation, deployment, and retraining jobs. This cluster covers dependencies, retries, scheduling, and pipeline composition for ML lifecycle automation.",
          "slug": "workflow-orchestration-for-ml-pipelines",
          "source": "db"
        },
        "dimension_id": 54,
        "input_skill": "Airflow",
        "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": 265,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "CI/CD",
        "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": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "CI/CD",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure \u0026 Security Automation Frameworks",
          "id": 249,
          "rationale": "Frameworks and libraries for provisioning, configuring, and automating cloud security infrastructure.",
          "slug": "infrastructure-security-automation-frameworks",
          "source": "db"
        },
        "dimension_id": 249,
        "input_skill": "Terraform",
        "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": 286,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "Terraform",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 286,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code for ML",
          "id": 57,
          "rationale": "Tools for provisioning and managing ML infrastructure resources through code.",
          "slug": "infrastructure-as-code-for-ml",
          "source": "db"
        },
        "dimension_id": 57,
        "input_skill": "Terraform",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 286,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "S3",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
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