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Pipeline run

62488b38-392a-4d2c-a3f0-3a810ee44b2d

Pipeline LLM cost (USD)
API 1: $0.0109 API 2: $0.0016 API 3: $0.0000 Total: $0.0126

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Data Management & Business Intelligence
Design and build master data/BI platforms: ETL, integrations, data models, dashboards, and analytics for business users, then troubleshoot, deploy, and support them in production.
"Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems"
Tech stack maturity
Mainstream Modern
The skill mix centers on current enterprise data and integration platforms such as APIs, microservices, Power BI, Informatica, and machine learning, which aligns with mainstream modern architecture rather than bleeding-edge or legacy-only stacks.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 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): Machine Learning
Evidence — skills matched in JD (46)
Business Intelligence Data Management Data Storage Technologies Distributed File Systems Data Processing APIs Connectors Batch Processing Real-Time Data Transfer Data Warehousing Enterprise Data Architecture Logical Modeling Physical Modeling Data Persistence Technologies Data Analysis Master Data Management ETL Metadata Layer Presentation Layer Security Administration Machine Learning Machine Learning Algorithms Microservices Search Before Create +21
Skill cluster (4 dimension groups, role-scoped)
AI Governance and Model Security
Machine Learning
API Integration and Data Fetching
API Integration
Observability and Incident Response
Dashboards
Cross-cutting / unaligned
Business Intelligence Data Management Data Storage Technologies Distributed File Systems Data Processing APIs Connectors Batch Processing Real-Time Data Transfer Data Warehousing Enterprise Data Architecture Logical Modeling Physical Modeling Data Persistence Technologies Data Analysis Master Data Management ETL Metadata Layer Presentation Layer Security Administration Machine Learning Algorithms Microservices Search Before Create De-Duplication Mass Record Processing Reporting Services Reports Scripting Informatica SAP PiLog Reltio Multi-domain Master Data Management Power BI Qlik Compose Informatica PowerCenter Azure SQL Database Azure Data Warehouse Azure Data Factory Azure Data Lake Azure Databricks Data Storytelling
Show KRA description ↓
• Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems, enabling stakeholders to manage the business and make effective decisions. • Building secure, available, scalable, stable and cost-effective master data solutions using data storage technologies, distributed file system, data processing, and business intelligence best practices. • Working with business customers in understanding the business requirements and implementing solutions to support process, analytical and reporting needs. • Designs and builds complex integration roadmaps leveraging APIs, Connectors, Batch and Real-Time data transfer. • Harness creativity to render information useful in data storytelling. • Designing and planning for solutions in the various engineering subject areas as it relates to data storage and movement solutions: data warehousing, enterprise system data architecture, data design (e.g., Logical and Physical Modeling), data persistence technologies, data processing, data management, and data analysis. • Launch and support new master data models that provide intuitive analytics to internal customers. • All aspects of the EDW: ETL, metadata layer, presentation layer, security/administration, user support and production support • Develop and Integrate Advance Analytics Solutions using Machine Learning Algorithms • Deploy and Develop Master Data Microservices, Search Before Create Capabilities in Customer facing applications, De-Duplication Prevention, Mass Record Processing and Updating in multiple Source Systems, 3rd Party Data Provider Real-time / Batch integration. • Build Reports/Dashboards that enable end business users to make day-to-day decisions. • Lead complex integration projects. • Provide Ad-Hoc reports and insights when needed. • Automate processes using ETL and scripting best practices. • 7-10+ years of hands-on experience working with industry leading tools within the Master Data Management discipline / data platform space (Informatica, SAP, PiLog, Reltio, etc..) with a demonstrated understanding of the following technologies: • Multi-domain Master Data Management • API Integration • Microservices • Reporting Services • 5+ years of experience in three or more of the following technologies: • Self-Service BI Tools: Power BI • Data Integration: Qlik Compose, Informatica Power Center • Azure: Azure SQL Database, Azure Data Warehouse and Azure Data Factory • Azure Big Data Technologies: Azure Data Lake and Azure Databricks

Signals

Skill scala-backend-developer
0.04
Alias
KRA data-engineer
0.61

Post-classification

Centroidupdated · n=1
Alias collision log
New-role queue
New skills captured39
New KRA capturedyes

Captured for admin review

Business Intelligence primary Data Governance Engineer pending
Data Management primary Data Governance Engineer pending
Data Storage Technologies primary Data Governance Engineer pending
Distributed File Systems primary Data Governance Engineer pending
Data Processing primary Data Governance Engineer pending
Connectors primary Data Governance Engineer pending
Batch Processing primary Data Governance Engineer pending
Real-Time Data Transfer primary Data Governance Engineer pending
Data Storytelling Data Governance Engineer pending
Data Warehousing primary Data Governance Engineer pending
Enterprise Data Architecture primary Data Governance Engineer pending
Logical Modeling primary Data Governance Engineer pending
Physical Modeling primary Data Governance Engineer pending
Data Persistence Technologies primary Data Governance Engineer pending
Data Analysis primary Data Governance Engineer pending
Master Data Management primary Data Governance Engineer pending
ETL primary Data Governance Engineer pending
Metadata Layer primary Data Governance Engineer pending
Presentation Layer primary Data Governance Engineer pending
Security primary Data Governance Engineer pending
Administration primary Data Governance Engineer pending
Machine Learning Algorithms primary Data Governance Engineer pending
Search Before Create primary Data Governance Engineer pending
De-Duplication primary Data Governance Engineer pending
Mass Record Processing primary Data Governance Engineer pending
Reporting Services primary Data Governance Engineer pending
Reports primary Data Governance Engineer pending
Scripting primary Data Governance Engineer pending
SAP primary Data Governance Engineer pending
PiLog primary Data Governance Engineer pending
Reltio primary Data Governance Engineer pending
Multi-domain Master Data Management primary Data Governance Engineer pending
Qlik Compose primary Data Governance Engineer pending
Informatica PowerCenter primary Data Governance Engineer pending
Azure SQL Database primary Data Governance Engineer pending
Azure Data Warehouse primary Data Governance Engineer pending
Azure Data Factory primary Data Governance Engineer pending
Azure Data Lake primary Data Governance Engineer pending
Azure Databricks primary Data Governance Engineer pending
R&R fragment (sim 0.00) Data Governance Engineer pending

• Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems, enabling stakeholders to manage the business and make effective deci…

Status: completed Created: 2026-05-27T13:40:36.070946Z Updated: 2026-05-27T13:44:11.634074Z API 3 duration: 25094 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 Governance Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: data-governance-engineer · id: 146 · source: db

Domain=Data Engineering & Analytics; The JD is centered on master data management, data governance, data quality, and master data solutions with integration and microservices, which best matches Data Governance Engineer.

Matched skills

master data managementInformaticaSAPPiLogReltioPower BIQlik ComposeInformatica Power CenterAzure SQL DatabaseAzure Data WarehouseAzure Data FactoryAPI IntegrationMicroservicesETLMachine Learning Algorithms

Matched dimensions

Master Data ManagementData Governance and Data QualityData Integration ArchitectureBusiness Intelligence ReportingData WarehousingData ModelingReal-time and Batch Data MovementAnalytics Enablement

Matched KRAs

Designing, developing, troubleshooting, evaluating, deploying, and documenting data managementBuilding secure, available, scalable, stable and cost-effective master data solutionsWorking with business customers in understanding the business requirementsDesigns and builds complex integration roadmaps leveraging APIs, ConnectorsLaunch and support new master data modelsAll aspects of the EDW: ETL, metadata layer, presentation layerDevelop and Integrate Advance Analytics Solutions using Machine Learning AlgorithmsDeploy and Develop Master Data MicroservicesBuild Reports/Dashboards that enable end business usersAutomate processes using ETL and scripting best practices

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
2
Skipped

Job description

Job Duties
 
• Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems, enabling stakeholders to manage the business and make effective decisions.
• Building secure, available, scalable, stable and cost-effective master data solutions using data storage technologies, distributed file system, data processing, and business intelligence best practices.
• Working with business customers in understanding the business requirements and implementing solutions to support process, analytical and reporting needs.
• Designs and builds complex integration roadmaps leveraging APIs, Connectors, Batch and Real-Time data transfer.
• Harness creativity to render information useful in data storytelling.
• Designing and planning for solutions in the various engineering subject areas as it relates to data storage and movement solutions: data warehousing, enterprise system data architecture, data design (e.g., Logical and Physical Modeling), data persistence technologies, data processing, data management, and data analysis.
• Launch and support new master data models that provide intuitive analytics to internal customers.
• All aspects of the EDW: ETL, metadata layer, presentation layer, security/administration, user support and production support
• Develop and Integrate Advance Analytics Solutions using Machine Learning Algorithms
• Deploy and Develop Master Data Microservices, Search Before Create Capabilities in Customer facing applications, De-Duplication Prevention, Mass Record Processing and Updating in multiple Source Systems, 3rd Party Data Provider Real-time / Batch integration.
• Build Reports/Dashboards that enable end business users to make day-to-day decisions.
• Lead complex integration projects.
• Provide Ad-Hoc reports and insights when needed.
• Automate processes using ETL and scripting best practices. 


Core Skills 
 
• 7-10+ years of hands-on experience working with industry leading tools within the Master Data Management discipline / data platform space (Informatica, SAP, PiLog, Reltio, etc..) with a demonstrated understanding of the following technologies: 
• Multi-domain Master Data Management
• API Integration
• Microservices
• Reporting Services
• 5+ years of experience in three or more of the following technologies: 
• Self-Service BI Tools: Power BI
• Data Integration: Qlik Compose, Informatica Power Center
• Azure: Azure SQL Database, Azure Data Warehouse and Azure Data Factory
• Azure Big Data Technologies: Azure Data Lake and Azure Databricks


If interested, please share your resume @ aman.gupta@insight.com

Skills from this JD

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

Business Intelligence 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Management 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Storage Technologies 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Distributed File Systems 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Processing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
APIs Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: APIs id=1192 · apis

Aliases — catalog

  • APIs (CANONICAL)

Context tags (catalog)

API Gateway Endpoint GraphQL JSON JWT Microservices OAuth Postman REST Rate Limiting SOAP Swagger Throttling Webhooks XML

Stored enrichment (catalog DB)

Category
Protocol
Sub-category
Application Programming Interfaces
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: APIs are a hiring-pipeline staple across backend, mobile, and platform JDs; REST/GraphQL/API design appears in large volumes of job postings and vendor docs, indicating broad adoption.

Skill profile (library / DB)

Skill nature
PROTOCOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
10
Sub-category id
902
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)
Connectors 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Batch Processing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

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

Skill enrichment (orchestrator / LLM)

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

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

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Enterprise Data Architecture 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Logical 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
Physical Modeling 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Persistence Technologies 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Analysis 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Master Data Management 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ETL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Metadata Layer 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Presentation Layer 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Security 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Administration 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Machine Learning Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Machine Learning id=1356 · machine-learning

Aliases — catalog

  • Machine Learning (CANONICAL)

Context tags (catalog)

Keras PyTorch TensorFlow cross-validation data preprocessing ensemble methods feature engineering hyperparameter tuning model evaluation natural language processing neural networks reinforcement learning scikit-learn supervised learning unsupervised learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Machine Learning
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1024
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • AI Governance and Model Security Catalog dimension db id 50

    Library dimension (catalog)

    Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning Algorithms 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Microservices Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: microservices id=41 · microservices

Aliases — catalog

  • microservices (CANONICAL) primary

Context tags (catalog)

API Gateway API gateway CQRS DevOps Docker Kubernetes REST API RESTful services Saga pattern Spring Boot circuit breaker containerization decentralized distributed tracing domain-driven design event sourcing event-driven event-driven architecture gRPC load balancing message broker microservices patterns monitoring scalability service discovery service mesh

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Distributed System Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Microservices and Distributed Systems Catalog dimension db id 9

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Search Before Create 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
De-Duplication 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Mass Record Processing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Reporting Services 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Dashboards Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: dashboards id=2455 · dashboards

Aliases — catalog

  • dashboards (CANONICAL) primary

Context tags (catalog)

BI tools Grafana KPI KPI tracking Looker Power BI Tableau UX design alerting analytics custom widgets dashboard design data aggregation data insights data sources data storytelling data visualization interactive dashboards metrics performance metrics performance tracking real-time analytics real-time monitoring reporting user interface

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Dashboarding
Confidence
0.80
Version strategy
NOT_APPLICABLE

Maturity reasoning: Dashboarding is a common requirement in BI/observability JDs and is supported by major vendors like Grafana, Power BI, and Tableau, indicating broad market adoption rather than a niche toolset.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
3485
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Backend Observability, Logging, and Diagnostics Catalog dimension db id 388

    Library dimension (catalog)

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

  • Observability and Incident Response Catalog dimension db id 10

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Reports 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Scripting Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

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

Aliases — catalog

  • Informatica (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SAP 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
PiLog 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Reltio 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Multi-domain Master Data Management 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
API Integration Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: API Integration id=1607 · api-integration

Aliases — catalog

  • API Integration (CANONICAL)

Context tags (catalog)

API Gateway Authentication Data Mapping Endpoint GraphQL JSON Microservices OAuth Postman REST Rate Limiting SOAP Swagger Webhooks XML

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Api Integration
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: API integration appears in a large share of software engineering JDs and is a standard requirement across backend, frontend, and platform roles; it is a core hiring-pipeline skill rather than a niche tool.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1210
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Integration and Data Fetching Catalog dimension db id 127

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer

  • Cross-Platform App Languages Catalog dimension db id 167

    Library dimension (catalog)

    Roles linked in library: Hybrid Mobile Developer

  • Networking and API Integration Catalog dimension db id 84

    Library dimension (catalog)

    Roles linked in library: Android Developer, Hybrid Mobile Developer, Native Mobile Developer, iOS Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Networking and API Integration
networking-and-api-integration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Power BI Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Power BI id=151 · power-bi

Aliases — catalog

  • Power BI (CANONICAL) primary

Context tags (catalog)

Azure Synapse DAX DirectQuery Import mode M language Power Query RLS SQL Server SSAS dashboard data modeling data warehouse gateway reporting star schema

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Bi Analytics Platform
Vendor
Microsoft
License
proprietary
Year introduced
2015
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Power BI appears frequently in BI/data analyst job descriptions and is a standard Microsoft analytics platform in enterprise stacks, with strong vendor support and broad adoption.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • BI and Visualization Tools Catalog dimension db id 31

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Qlik Compose 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Informatica PowerCenter 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure SQL Database 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Data Warehouse 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Data Factory 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Data Lake 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
Other
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Databricks 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
Other
Sub-category
general
Skill nature
TOOL
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
APIs in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Logical Modeling new
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Logical 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
Machine Learning in_db
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Dashboards in_db
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Dashboards in_db
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Informatica in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Integration in_db
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Integration in_db
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Integration in_db
Networking and API Integration
networking-and-api-integration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Power BI in_db
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Business Intelligence | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Management | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Storage Technologies | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Distributed File Systems | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Processing | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Connectors | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Batch Processing | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Real-Time Data Transfer | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Storytelling | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Warehousing | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Enterprise Data Architecture | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Physical Modeling | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Persistence Technologies | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Analysis | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Master Data Management | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ETL | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Metadata Layer | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Presentation Layer | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Security | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Administration | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Machine Learning Algorithms | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Search Before Create | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed De-Duplication | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Mass Record Processing | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Reporting Services | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Reports | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Scripting | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed SAP | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed PiLog | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Reltio | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Multi-domain Master Data Management | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Qlik Compose | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Informatica PowerCenter | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure SQL Database | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure Data Warehouse | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure Data Factory | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure Data Lake | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure Databricks | type=Other subtype=general nature=TOOL lifespan=MULTI_YEAR
dimension_skill_link_proposed Logical Modeling ↔ Application Architecture Patterns
dimension_skill_link_proposed Logical Modeling ↔ Service Architecture and Design Patterns
nano JD Parser — gpt-4.1-nano click to toggle
CompanyInsight
Experience7-10+ years of hands-on experience
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": "Insight",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": 10,
    "min": 7,
    "raw": "7-10+ years of hands-on experience"
  },
  "job_locations": [],
  "role": null,
  "role_aliases": [],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 13,
      "heading": "Job Duties",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Designing, developing, troubleshooting, evaluating,",
        "last_5_words": "ETL and scripting best practices."
      },
      "text": "\u2022 Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems, enabling stakeholders to manage the business and make effective decisions.\n\u2022 Building secure, available, scalable, stable and cost-effective master data solutions using data storage technologies, distributed file system, data processing, and business intelligence best practices.\n\u2022 Working with business customers in understanding the business requirements and implementing solutions to support process, analytical and reporting needs.\n\u2022 Designs and builds complex integration roadmaps leveraging APIs, Connectors, Batch and Real-Time data transfer.\n\u2022 Harness creativity to render information useful in data storytelling.\n\u2022 Designing and planning for solutions in the various engineering subject areas as it relates to data storage and movement solutions: data warehousing, enterprise system data architecture, data design (e.g., Logical and Physical Modeling), data persistence technologies, data processing, data management, and data analysis.\n\u2022 Launch and support new master data models that provide intuitive analytics to internal customers.\n\u2022 All aspects of the EDW: ETL, metadata layer, presentation layer, security/administration, user support and production support\n\u2022 Develop and Integrate Advance Analytics Solutions using Machine Learning Algorithms\n\u2022 Deploy and Develop Master Data Microservices, Search Before Create Capabilities in Customer facing applications, De-Duplication Prevention, Mass Record Processing and Updating in multiple Source Systems, 3rd Party Data Provider Real-time / Batch integration.\n\u2022 Build Reports/Dashboards that enable end business users to make day-to-day decisions.\n\u2022 Lead complex integration projects.\n\u2022 Provide Ad-Hoc reports and insights when needed.\n\u2022 Automate processes using ETL and scripting best practices.",
      "word_count": 284
    },
    {
      "bullet_count": 8,
      "heading": "Core Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 7-10+ years of hands-on",
        "last_5_words": "Azure Data Lake and Azure Databricks"
      },
      "text": "\u2022 7-10+ years of hands-on experience working with industry leading tools within the Master Data Management discipline / data platform space (Informatica, SAP, PiLog, Reltio, etc..) with a demonstrated understanding of the following technologies: \n\u2022 Multi-domain Master Data Management\n\u2022 API Integration\n\u2022 Microservices\n\u2022 Reporting Services\n\u2022 5+ years of experience in three or more of the following technologies: \n\u2022 Self-Service BI Tools: Power BI\n\u2022 Data Integration: Qlik Compose, Informatica Power Center\n\u2022 Azure: Azure SQL Database, Azure Data Warehouse and Azure Data Factory\n\u2022 Azure Big Data Technologies: Azure Data Lake and Azure Databricks",
      "word_count": 134
    }
  ],
  "urls": [
    {
      "type": "other",
      "url": "mailto:aman.gupta@insight.com"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Business Intelligence"
    },
    {
      "is_primary": true,
      "skill_name": "Data Management"
    },
    {
      "is_primary": true,
      "skill_name": "Data Storage Technologies"
    },
    {
      "is_primary": true,
      "skill_name": "Distributed File Systems"
    },
    {
      "is_primary": true,
      "skill_name": "Data Processing"
    },
    {
      "is_primary": true,
      "skill_name": "APIs"
    },
    {
      "is_primary": true,
      "skill_name": "Connectors"
    },
    {
      "is_primary": true,
      "skill_name": "Batch Processing"
    },
    {
      "is_primary": true,
      "skill_name": "Real-Time Data Transfer"
    },
    {
      "is_primary": false,
      "skill_name": "Data Storytelling"
    },
    {
      "is_primary": true,
      "skill_name": "Data Warehousing"
    },
    {
      "is_primary": true,
      "skill_name": "Enterprise Data Architecture"
    },
    {
      "is_primary": true,
      "skill_name": "Logical Modeling"
    },
    {
      "is_primary": true,
      "skill_name": "Physical Modeling"
    },
    {
      "is_primary": true,
      "skill_name": "Data Persistence Technologies"
    },
    {
      "is_primary": true,
      "skill_name": "Data Analysis"
    },
    {
      "is_primary": true,
      "skill_name": "Master Data Management"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "Metadata Layer"
    },
    {
      "is_primary": true,
      "skill_name": "Presentation Layer"
    },
    {
      "is_primary": true,
      "skill_name": "Security"
    },
    {
      "is_primary": true,
      "skill_name": "Administration"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning Algorithms"
    },
    {
      "is_primary": true,
      "skill_name": "Microservices"
    },
    {
      "is_primary": true,
      "skill_name": "Search Before Create"
    },
    {
      "is_primary": true,
      "skill_name": "De-Duplication"
    },
    {
      "is_primary": true,
      "skill_name": "Mass Record Processing"
    },
    {
      "is_primary": true,
      "skill_name": "Reporting Services"
    },
    {
      "is_primary": true,
      "skill_name": "Dashboards"
    },
    {
      "is_primary": true,
      "skill_name": "Reports"
    },
    {
      "is_primary": true,
      "skill_name": "Scripting"
    },
    {
      "is_primary": true,
      "skill_name": "Informatica"
    },
    {
      "is_primary": true,
      "skill_name": "SAP"
    },
    {
      "is_primary": true,
      "skill_name": "PiLog"
    },
    {
      "is_primary": true,
      "skill_name": "Reltio"
    },
    {
      "is_primary": true,
      "skill_name": "Multi-domain Master Data Management"
    },
    {
      "is_primary": true,
      "skill_name": "API Integration"
    },
    {
      "is_primary": true,
      "skill_name": "Power BI"
    },
    {
      "is_primary": true,
      "skill_name": "Qlik Compose"
    },
    {
      "is_primary": true,
      "skill_name": "Informatica PowerCenter"
    },
    {
      "is_primary": true,
      "skill_name": "Azure SQL Database"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Warehouse"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Factory"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Lake"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Databricks"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": "Insight",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": 10,
      "min": 7,
      "raw": "7-10+ years of hands-on experience"
    },
    "job_locations": [],
    "role": null,
    "role_aliases": [],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 13,
        "heading": "Job Duties",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Designing, developing, troubleshooting, evaluating,",
          "last_5_words": "ETL and scripting best practices."
        },
        "text": "\u2022 Designing, developing, troubleshooting, evaluating, deploying, and documenting data management and business intelligence systems, enabling stakeholders to manage the business and make effective decisions.\n\u2022 Building secure, available, scalable, stable and cost-effective master data solutions using data storage technologies, distributed file system, data processing, and business intelligence best practices.\n\u2022 Working with business customers in understanding the business requirements and implementing solutions to support process, analytical and reporting needs.\n\u2022 Designs and builds complex integration roadmaps leveraging APIs, Connectors, Batch and Real-Time data transfer.\n\u2022 Harness creativity to render information useful in data storytelling.\n\u2022 Designing and planning for solutions in the various engineering subject areas as it relates to data storage and movement solutions: data warehousing, enterprise system data architecture, data design (e.g., Logical and Physical Modeling), data persistence technologies, data processing, data management, and data analysis.\n\u2022 Launch and support new master data models that provide intuitive analytics to internal customers.\n\u2022 All aspects of the EDW: ETL, metadata layer, presentation layer, security/administration, user support and production support\n\u2022 Develop and Integrate Advance Analytics Solutions using Machine Learning Algorithms\n\u2022 Deploy and Develop Master Data Microservices, Search Before Create Capabilities in Customer facing applications, De-Duplication Prevention, Mass Record Processing and Updating in multiple Source Systems, 3rd Party Data Provider Real-time / Batch integration.\n\u2022 Build Reports/Dashboards that enable end business users to make day-to-day decisions.\n\u2022 Lead complex integration projects.\n\u2022 Provide Ad-Hoc reports and insights when needed.\n\u2022 Automate processes using ETL and scripting best practices.",
        "word_count": 284
      },
      {
        "bullet_count": 8,
        "heading": "Core Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 7-10+ years of hands-on",
          "last_5_words": "Azure Data Lake and Azure Databricks"
        },
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}
API 2 — extract-details
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              "role_archetype": null,
              "slug": "web-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cross-Platform App Languages",
            "id": 167,
            "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
            "slug": "cross-platform-app-languages",
            "source": "db"
          },
          "input_skill": "API Integration",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Hybrid Mobile Developer",
              "id": 11,
              "rationale": null,
              "role_archetype": null,
              "slug": "hybrid-mobile-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Networking and API Integration",
            "id": 84,
            "rationale": "Client-side HTTP communication with backend services, including request construction, response parsing, retries, and error handling. iOS engineers use this to connect native screens to server-owned APIs.",
            "slug": "networking-and-api-integration",
            "source": "db"
          },
          "input_skill": "API Integration",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Android Developer",
              "id": 4,
              "rationale": null,
              "role_archetype": null,
              "slug": "android-engineer",
              "source": "db"
            },
            {
              "display_name": "Hybrid Mobile Developer",
              "id": 11,
              "rationale": null,
              "role_archetype": null,
              "slug": "hybrid-mobile-developer",
              "source": "db"
            },
            {
              "display_name": "Native Mobile Developer",
              "id": 75,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "native-mobile-developer",
              "source": "db"
            },
            {
              "display_name": "iOS Developer",
              "id": 6,
              "rationale": null,
              "role_archetype": null,
              "slug": "ios-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "API Integration",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Power BI",
          "alias_type": "CANONICAL",
          "id": 360,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "Power BI",
        "id": 151,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "power-bi",
        "sub_category_id": 111,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "BI and Visualization Tools",
            "id": 31,
            "rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
            "slug": "bi-and-visualization-tools",
            "source": "db"
          },
          "input_skill": "Power BI",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Power BI",
      "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": "Qlik Compose",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "qlik-compose",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Informatica PowerCenter",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "informatica-powercenter",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure SQL Database",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-sql-database",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure Data Warehouse",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-data-warehouse",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure Data Factory",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-data-factory",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure Data Lake",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-data-lake",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure Databricks",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Other",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-databricks",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Business Intelligence",
    "Data Management",
    "Data Storage Technologies",
    "Distributed File Systems",
    "Data Processing",
    "Connectors",
    "Batch Processing",
    "Real-Time Data Transfer",
    "Data Storytelling",
    "Data Warehousing",
    "Enterprise Data Architecture",
    "Physical Modeling",
    "Data Persistence Technologies",
    "Data Analysis",
    "Master Data Management",
    "ETL",
    "Metadata Layer",
    "Presentation Layer",
    "Security",
    "Administration",
    "Machine Learning Algorithms",
    "Search Before Create",
    "De-Duplication",
    "Mass Record Processing",
    "Reporting Services",
    "Reports",
    "Scripting",
    "SAP",
    "PiLog",
    "Reltio",
    "Multi-domain Master Data Management",
    "Qlik Compose",
    "Informatica PowerCenter",
    "Azure SQL Database",
    "Azure Data Warehouse",
    "Azure Data Factory",
    "Azure Data Lake",
    "Azure Databricks"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Governance Engineer",
    "id": 146,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on master data management, data governance, data quality, and master data solutions with integration and microservices, which best matches Data Governance Engineer.",
    "role_archetype": null,
    "slug": "data-governance-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Business Intelligence",
      "tag": "new"
    },
    {
      "skill": "Data Management",
      "tag": "new"
    },
    {
      "skill": "Data Storage Technologies",
      "tag": "new"
    },
    {
      "skill": "Distributed File Systems",
      "tag": "new"
    },
    {
      "skill": "Data Processing",
      "tag": "new"
    },
    {
      "skill": "APIs",
      "tag": "in_db"
    },
    {
      "skill": "Connectors",
      "tag": "new"
    },
    {
      "skill": "Batch Processing",
      "tag": "new"
    },
    {
      "skill": "Real-Time Data Transfer",
      "tag": "new"
    },
    {
      "skill": "Data Storytelling",
      "tag": "new"
    },
    {
      "skill": "Data Warehousing",
      "tag": "new"
    },
    {
      "skill": "Enterprise Data Architecture",
      "tag": "new"
    },
    {
      "skill": "Logical Modeling",
      "tag": "in_db"
    },
    {
      "skill": "Physical Modeling",
      "tag": "new"
    },
    {
      "skill": "Data Persistence Technologies",
      "tag": "new"
    },
    {
      "skill": "Data Analysis",
      "tag": "new"
    },
    {
      "skill": "Master Data Management",
      "tag": "new"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Metadata Layer",
      "tag": "new"
    },
    {
      "skill": "Presentation Layer",
      "tag": "new"
    },
    {
      "skill": "Security",
      "tag": "new"
    },
    {
      "skill": "Administration",
      "tag": "new"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "Machine Learning Algorithms",
      "tag": "new"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "Search Before Create",
      "tag": "new"
    },
    {
      "skill": "De-Duplication",
      "tag": "new"
    },
    {
      "skill": "Mass Record Processing",
      "tag": "new"
    },
    {
      "skill": "Reporting Services",
      "tag": "new"
    },
    {
      "skill": "Dashboards",
      "tag": "in_db"
    },
    {
      "skill": "Reports",
      "tag": "new"
    },
    {
      "skill": "Scripting",
      "tag": "new"
    },
    {
      "skill": "Informatica",
      "tag": "in_db"
    },
    {
      "skill": "SAP",
      "tag": "new"
    },
    {
      "skill": "PiLog",
      "tag": "new"
    },
    {
      "skill": "Reltio",
      "tag": "new"
    },
    {
      "skill": "Multi-domain Master Data Management",
      "tag": "new"
    },
    {
      "skill": "API Integration",
      "tag": "in_db"
    },
    {
      "skill": "Power BI",
      "tag": "in_db"
    },
    {
      "skill": "Qlik Compose",
      "tag": "new"
    },
    {
      "skill": "Informatica PowerCenter",
      "tag": "new"
    },
    {
      "skill": "Azure SQL Database",
      "tag": "new"
    },
    {
      "skill": "Azure Data Warehouse",
      "tag": "new"
    },
    {
      "skill": "Azure Data Factory",
      "tag": "new"
    },
    {
      "skill": "Azure Data Lake",
      "tag": "new"
    },
    {
      "skill": "Azure Databricks",
      "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": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "APIs",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1192,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "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"
        },
        "dimension_id": 293,
        "input_skill": "Logical Modeling",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".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"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 146,
        "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"
        },
        "dimension_id": 18,
        "input_skill": "Logical Modeling",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "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"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "AI Governance and Model Security",
          "id": 50,
          "rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
          "slug": "ai-governance-and-model-security",
          "source": "db"
        },
        "dimension_id": 50,
        "input_skill": "Machine Learning",
        "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"
          },
          {
            "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": 1356,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Machine Learning",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1356,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Microservices and Distributed Systems",
          "id": 9,
          "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
          "slug": "microservices-and-distributed-systems",
          "source": "db"
        },
        "dimension_id": 9,
        "input_skill": "Microservices",
        "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",
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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",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-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": 41,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
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          "id": 388,
          "rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
          "slug": "backend-observability-logging-and-diagnostics",
          "source": "db"
        },
        "dimension_id": 388,
        "input_skill": "Dashboards",
        "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": "Kotlin Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-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": 2455,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
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          "source": "db"
        },
        "dimension_id": 10,
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        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
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            "source": "db"
          },
          {
            "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.",
            "slug": "backend-engineer",
            "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2455,
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        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "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": "Informatica",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 117,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "API Integration and Data Fetching",
          "id": 127,
          "rationale": "Client-side integration with backend endpoints and third-party services, including request shaping, response handling, and synchronization with UI state. This is central to frontend work because most screens depend on remote data.",
          "slug": "api-integration-and-data-fetching",
          "source": "db"
        },
        "dimension_id": 127,
        "input_skill": "API Integration",
        "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": "Angular Frontend Developer",
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            "rationale": null,
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          },
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            "rationale": null,
            "role_archetype": null,
            "slug": "frontend-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": "React Frontend Developer",
            "id": 89,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "react-frontend-developer",
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          },
          {
            "display_name": "Svelte Frontend Developer",
            "id": 92,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "svelte-frontend-developer",
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          },
          {
            "display_name": "Vue Frontend Developer",
            "id": 91,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "vue-frontend-developer",
            "source": "db"
          },
          {
            "display_name": "Web Developer",
            "id": 25,
            "rationale": null,
            "role_archetype": null,
            "slug": "web-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1607,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 146,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cross-Platform App Languages",
          "id": 167,
          "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
          "slug": "cross-platform-app-languages",
          "source": "db"
        },
        "dimension_id": 167,
        "input_skill": "API Integration",
        "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": "Hybrid Mobile Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "hybrid-mobile-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1607,
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      },
      {
        "chosen_role_id": 146,
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          "slug": "networking-and-api-integration",
          "source": "db"
        },
        "dimension_id": 84,
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        "matched_chosen_role": false,
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        "roles_from_db": [
          {
            "display_name": "Android Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "android-engineer",
            "source": "db"
          },
          {
            "display_name": "Hybrid Mobile Developer",
            "id": 11,
            "rationale": null,
            "role_archetype": null,
            "slug": "hybrid-mobile-developer",
            "source": "db"
          },
          {
            "display_name": "Native Mobile Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "native-mobile-developer",
            "source": "db"
          },
          {
            "display_name": "iOS Developer",
            "id": 6,
            "rationale": null,
            "role_archetype": null,
            "slug": "ios-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1607,
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        "skipped_reason": null
      },
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        "chosen_role_id": 146,
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          "rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
          "slug": "bi-and-visualization-tools",
          "source": "db"
        },
        "dimension_id": 31,
        "input_skill": "Power BI",
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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": "Data Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 151,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 2
  },
  "planner_output": null,
  "run_id": "62488b38-392a-4d2c-a3f0-3a810ee44b2d"
}

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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