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Pipeline run

fd2cce53-d033-43a3-bbc1-06f0aa10f0de

Pipeline LLM cost (USD)
API 1: $0.0099 API 2: $0.0008 API 3: $0.0000 Total: $0.0107

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · BI Architecture / Data Warehousing
Designs and builds BI/data warehouse solutions in Microsoft/Azure stacks, including ETL, data modeling, data quality/MDM, and Power BI reporting. Also scopes costs, reviews technical choices with stakeholders, and mentors developers on BI patterns.
"Analyzes and designs BI solutions"
Tech stack maturity
Mainstream Modern
The stack centers on Power BI, SQL Server, star-schema modeling, and lakehouse concepts, which together indicate a broadly modern but not bleeding-edge cloud-native BI environment.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (31)
BI Data Warehousing Data Modeling ETL Data Lake Data Visualization Master Data Management Data Quality Management SQL Server SQL Server Analysis Services Tabular SQL Server Integration Services SQL Server Master Data Services SQL Server Data Quality Services DAX T-SQL Power BI Power Query M language Power Pivot Azure Data Lake Azure SQL Database Azure Data Factory Azure Databricks Azure Synapse +6
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
BI Data Warehousing Data Modeling ETL Data Lake Data Visualization Master Data Management Data Quality Management SQL Server SQL Server Analysis Services Tabular SQL Server Integration Services SQL Server Master Data Services SQL Server Data Quality Services DAX T-SQL Power BI Power Query M language Power Pivot Azure Data Lake Azure SQL Database Azure Data Factory Azure Databricks Azure Synapse Azure SQL Warehouse Lakehouse Star Schema Snowflake Schema Slowly Changing Dimension Agile
Show KRA description ↓
Analyzes and designs BI solutions Develops BI solutions in a team environment Performs technology, research, evaluation and selection Advises IT management on technical strategies, design patterns and practices relevant to BI software development Aligns BI solution designs to corporate and IT strategy through analysis and technical review processes Estimates project and solution costs through scoping exercises Advocate for corporate and IT BI objectives and the technology that implements them Mentors developers and other software development staff on the use of BI technology to solve business problems. Design Data prep patterns and practices ETL and LET design patterns Reliable batch data processing Modern data modeling patterns and practices Dimensional data store schemas (star/snowflake) Standard data warehousing processes, patterns and practices Slowly Changing Dimension (SCD) analysis and development strategies Data Lake designs Data visualization patterns and practices Master Data Management (MDM): processes, patterns and practices for implementing a Master Data Management strategy in the context of a BI strategy. Data Quality Management: processes, patterns and practices for implementing a Data Quality Management strategy in the context of a BI strategy. Microsoft BI stack SQL Server RDBMS SQL Server Analysis Services Tabular SQL Server Integration Services SQL Server Master Data Services SQL Server Data Quality Services Data Analysis Expressions (DAX) language T-SQL Power BI (Administration and Development) Power Query & M language Power Pivot Azure Data Lake Azure SQL Database Azure Data Factory Azure Data Bricks Azure Synapse (Serverless and/or Dedicated) Azure SQL Warehouse All of the following experience requirements involve active development of systems and solutions deployed to production environments. Technical 7+ years in BI Architecture, Data Warehousing, and Data Modeling 5+ years of data- and BI-specific business analysis 5+ years devoted to the Microsoft BI Stack (SSIS, SSAS, etc.) 3+ years creating solutions in the Azure space using Lakehouse design patterns Business/Domain Experience in at least some of the following business data domains are expected given the listed technical experience above. Finance & Accounting GL, AR Human Resources Payroll, Absence, Benefits Project Management Costs, revenue, planned vs. actual etc. Procure-to-Pay Invoice aging Sales Opportunity management Excellent English oral and written communication skills Business analysis and requirements gathering techniques and practices Facility in managing stakeholder/SME relationships and building business partnerships Ability to collaborate effectively with technical and non-technical people, including those at the highest levels of the organization Uses Agile software methodologies for work execution and team collaboration

Signals

Skill data-engineer
0.06
Alias
KRA data-engineer
0.61

Post-classification

Centroidupdated · n=12
Alias collision log
New-role queue
New skills captured26
New KRA capturedyes

Captured for admin review

BI primary BI Developer pending
Data Warehousing primary BI Developer pending
Data Modeling primary BI Developer pending
ETL primary BI Developer pending
Data Lake primary BI Developer pending
Data Visualization primary BI Developer pending
Master Data Management primary BI Developer pending
Data Quality Management primary BI Developer pending
SQL Server Analysis Services primary BI Developer pending
Tabular primary BI Developer pending
SQL Server Integration Services primary BI Developer pending
SQL Server Master Data Services primary BI Developer pending
SQL Server Data Quality Services primary BI Developer pending
DAX primary BI Developer pending
T-SQL primary BI Developer pending
Power Query primary BI Developer pending
M language primary BI Developer pending
Power Pivot primary BI Developer pending
Azure Data Lake primary BI Developer pending
Azure SQL Database primary BI Developer pending
Azure Data Factory primary BI Developer pending
Azure Databricks primary BI Developer pending
Azure Synapse primary BI Developer pending
Azure SQL Warehouse primary BI Developer pending
Snowflake Schema primary BI Developer pending
Slowly Changing Dimension primary BI Developer pending
R&R fragment (sim 0.00) BI Developer pending

Analyzes and designs BI solutions Develops BI solutions in a team environment Performs technology, research, evaluation and selection Advises IT management on technical strategies, design patterns and…

Status: completed Created: 2026-05-27T17:35:52.550639Z Updated: 2026-05-27T17:37:46.250517Z API 3 duration: 6625 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

BI Developer

domain · Data Engineering & Analytics CASE DOMAIN

slug: bi-developer · id: 147 · source: db

Domain=Data Engineering & Analytics; The JD centers on BI solution analysis/design, Microsoft BI stack development, Power BI/SSAS/SSIS work, and advising/mentoring on BI practices, which best matches BI Developer.

Matched skills

BI solutionsMicrosoft BI stackSQL Server RDBMSSQL Server Analysis Services TabularSQL Server Integration ServicesSQL Server Master Data ServicesSQL Server Data Quality ServicesDAXT-SQLPower BIPower QueryPower PivotAzure Data LakeAzure SQL DatabaseAzure Data Factory

Matched dimensions

BI solution architecture and developmentData warehousing and data modelingAzure-based BI implementationBI strategy and technical advisoryData visualization and reportingMaster data management and data quality

Matched KRAs

Analyzes and designs BI solutionsDevelops BI solutions in a team environmentPerforms technology research, evaluation and selectionAdvises IT management on technical strategiesAligns BI solution designs to corporate and IT strategyEstimates project and solution costsMentors developers on BI technologyDesign data prep patterns and practicesReliable batch data processingData visualization patterns and 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
6
Skipped

Job description

Duties/Responsibilities
Analyzes and designs BI solutionsDevelops BI solutions in a team environmentPerforms technology, research, evaluation and selectionAdvises IT management on technical strategies, design patterns and practices relevant to BI software developmentAligns BI solution designs to corporate and IT strategy through analysis and technical review processesEstimates project and solution costs through scoping exercisesAdvocate for corporate and IT BI objectives and the technology that implements themMentors developers and other software development staff on the use of BI technology to solve business problems.
Required Skills

Design  Data prep patterns and practicesETL and LET design patternsReliable batch data processingModern data modeling patterns and practicesDimensional data store schemas (star/snowflake)Standard data warehousing processes, patterns and practicesSlowly Changing Dimension (SCD) analysis and development strategiesData Lake designsData visualization patterns and practicesMaster Data Management (MDM): processes, patterns and practices for implementing a Master Data Management strategy in the context of a BI strategy.Data Quality Management: processes, patterns and practices for implementing a Data Quality Management strategy in the context of a BI strategy.
Technology Microsoft BI stackSQL Server RDBMSSQL Server Analysis Services TabularSQL Server Integration ServicesSQL Server Master Data ServicesSQL Server Data Quality ServicesData Analysis Expressions (DAX) languageT-SQLPower BI (Administration and Development)Power Query & M languagePower PivotAzure Data LakeAzure SQL DatabaseAzure Data FactoryAzure Data BricksAzure Synapse (Serverless and/or Dedicated)Azure SQL Warehouse
Related Experience

All of the following experience requirements involve active development of systems and solutions deployed to production environments.

Technical
7+ years in BI Architecture, Data Warehousing, and Data Modeling5+ years of data- and BI-specific business analysis5+ years devoted to the Microsoft BI Stack (SSIS, SSAS, etc.)3+ years creating solutions in the Azure space using Lakehouse design patterns
Business/Domain

Experience in at least some of the following business data domains are expected given the listed technical experience above.Finance & AccountingGL, ARHuman ResourcesPayroll, Absence, BenefitsProject ManagementCosts, revenue, planned vs. actual etc.Procure-to-PayInvoice agingSalesOpportunity management
Other Skills And Experience
Excellent English oral and written communication skillsBusiness analysis and requirements gathering techniques and practicesFacility in managing stakeholder/SME relationships and building business partnershipsAbility to collaborate effectively with technical and non-technical people, including those at the highest levels of the organizationUses Agile software methodologies for work execution and team collaboration
Primary Location

IN-IN-Chennai

Work Locations

INDChennai

Job

Technical and Professional

Organization

IND 204 GPS India

Schedule

Regular

Job Type

Full-time

Job Posting

May 4, 2022, 3:15:50 AM

Skills from this JD

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

BI Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

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

Skill enrichment (orchestrator / LLM)

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

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

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Application Architecture Patterns Catalog dimension db id 293

    Library dimension (catalog)

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

  • Service Architecture and Design Patterns Catalog dimension db id 18

    Library dimension (catalog)

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

API 3 link attempts (this skill)

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

Skill enrichment (orchestrator / LLM)

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

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

Aliases — catalog

  • Data Lakes (CANONICAL)

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

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

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Quality 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
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Server Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL Server id=18 · sql-server

Aliases — catalog

  • SQL Server (CANONICAL) primary
  • SQL Server 2000 (VERSION)
  • SQL Server 2005 (VERSION)
  • SQL Server 2008 (VERSION)
  • SQL Server 2012 (VERSION)
  • SQL Server 2014 (VERSION)
  • SQL Server 2016 (VERSION)
  • SQL Server 2017 (VERSION)
  • SQL Server 2019 (VERSION)
  • SQL Server 2022 (VERSION)
  • SQL Server 6.5 (VERSION)
  • SQL Server 7.0 (VERSION)

Context tags (catalog)

Always On CLR Integration Clustered Index ETL Execution Plan Linked Servers Query Store Replication SQL Agent SQL Server Agent SQL Server Integration Services SQL Server Management Studio SQL Server Reporting Services SSIS SSMS SSRS Stored Procedures T-SQL TempDB backup and recovery backup and restore clustering data migration data warehousing database design database normalization indexing performance tuning query optimization replication stored procedures transaction log transaction logs

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
Microsoft
License
proprietary
Year introduced
1989
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL Server appears in many enterprise job descriptions and remains a major Microsoft-supported RDBMS with active Azure SQL/SQL Server demand; it is a common hiring-pipeline staple, not a sunset technology.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Relational Database Design Catalog dimension db id 4

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Server Analysis 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
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Tabular Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Server Integration 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
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Server Master Data 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
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Server Data Quality 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
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
DAX 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
T-SQL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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)
Power Query Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
M language 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Power Pivot Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Synapse Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Synapse Analytics id=108 · azure-synapse-analytics

Aliases — catalog

  • Azure Synapse Analytics (CANONICAL) primary

Context tags (catalog)

Apache Spark Azure Data Lake Storage Data Factory Delta Lake PolyBase SQL pools Spark pools Synapse Studio T-SQL dedicated SQL pool linked services notebooks pipelines serverless SQL pool workspace

Stored enrichment (catalog DB)

Category
Service
Sub-category
Analytics Service
Vendor
Microsoft
License
proprietary
Year introduced
2019
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in cloud data-platform JDs and Microsoft’s Azure analytics stack; often listed alongside Databricks/ADF for warehousing and ETL, indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
117
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Data Warehouses Catalog dimension db id 22

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Data Warehouses
cloud-data-warehouses
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure SQL 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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Lakehouse Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Lakehouse id=1359 · lakehouse

Aliases — catalog

  • Lakehouse (CANONICAL)

Context tags (catalog)

Apache Spark Delta Lake ETL SQL analytics cloud storage data governance data integration data lake data modeling data pipeline data warehouse metadata management real-time processing streaming analytics

Stored enrichment (catalog DB)

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

Maturity reasoning: Lakehouse is increasingly listed in data-platform JDs and vendor docs (Databricks, Snowflake, Microsoft Fabric), but it is not yet as universal as core warehouse or lake skills.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1026
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)
Star Schema Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Star schema id=126 · star-schema

Aliases — catalog

  • Star schema (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Data Modeling and Schema Design Catalog dimension db id 26

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Snowflake Schema Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Slowly Changing Dimension Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Slowly changing dimensions id=128 · slowly-changing-dimensions

Aliases — catalog

  • Slowly changing dimensions (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Data Modeling and Schema Design Catalog dimension db id 26

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Modeling and Schema Design
data-modeling-and-schema-design
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

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

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

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
Data Modeling new
Application Architecture Patterns
application-architecture-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Modeling new
Service Architecture and Design Patterns
service-architecture-and-design-patterns
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Lake new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Lake new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
SQL Server in_db
Relational Database Design
relational-database-design
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)
Azure Synapse new
Cloud Data Warehouses
cloud-data-warehouses
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Lakehouse in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Star Schema in_db
Data Modeling and Schema Design
data-modeling-and-schema-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Slowly Changing Dimension new
Data Modeling and Schema Design
data-modeling-and-schema-design
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed BI | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Warehousing | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Visualization | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Master Data Management | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Quality Management | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed SQL Server Analysis Services | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Tabular | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed SQL Server Integration Services | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed SQL Server Master Data Services | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed SQL Server Data Quality Services | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed DAX | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed T-SQL | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed Power Query | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed M language | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed Power Pivot | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure Data Lake | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure SQL Database | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Data Factory | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Databricks | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure SQL Warehouse | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Snowflake Schema | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Data Modeling ↔ Application Architecture Patterns
dimension_skill_link_proposed Data Modeling ↔ Service Architecture and Design Patterns
dimension_skill_link_proposed Data Lake ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Data Lake ↔ React Frontend Development
dimension_skill_link_proposed Azure Synapse ↔ Cloud Data Warehouses
dimension_skill_link_proposed Slowly Changing Dimension ↔ Data Modeling and Schema Design
nano JD Parser — gpt-4.1-nano click to toggle
Experience7+ years in BI Architecture, Data Warehousing, and Data Modeling
DomainOther
Location Chennai, India (null)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
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      "domain": "Other"
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    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 7,
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  },
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      "aliases": [
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      "country": "India",
      "state": "null",
      "work_mode": "null"
    }
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  "role": null,
  "role_aliases": [],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 8,
      "heading": "Duties/Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Analyzes and designs BI solutionsDevelops",
        "last_5_words": "to solve business problems."
      },
      "text": "Analyzes and designs BI solutions\nDevelops BI solutions in a team environment\nPerforms technology, research, evaluation and selection\nAdvises IT management on technical strategies, design patterns and practices relevant to BI software development\nAligns BI solution designs to corporate and IT strategy through analysis and technical review processes\nEstimates project and solution costs through scoping exercises\nAdvocate for corporate and IT BI objectives and the technology that implements them\nMentors developers and other software development staff on the use of BI technology to solve business problems.",
      "word_count": 88
    },
    {
      "bullet_count": 11,
      "heading": "Required Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Design  Data prep patterns and",
        "last_5_words": "in the context of a BI strategy."
      },
      "text": "Design  Data prep patterns and practices\nETL and LET design patterns\nReliable batch data processing\nModern data modeling patterns and practices\nDimensional data store schemas (star/snowflake)\nStandard data warehousing processes, patterns and practices\nSlowly Changing Dimension (SCD) analysis and development strategies\nData Lake designs\nData visualization patterns and practices\nMaster Data Management (MDM): processes, patterns and practices for implementing a Master Data Management strategy in the context of a BI strategy.\nData Quality Management: processes, patterns and practices for implementing a Data Quality Management strategy in the context of a BI strategy.",
      "word_count": 104
    },
    {
      "bullet_count": 15,
      "heading": "Technology",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Microsoft BI stack\nSQL Server RDBMS\nSQL",
        "last_5_words": "and/or Dedicated)\nAzure SQL Warehouse"
      },
      "text": "Microsoft BI stack\nSQL Server RDBMS\nSQL Server Analysis Services Tabular\nSQL Server Integration Services\nSQL Server Master Data Services\nSQL Server Data Quality Services\nData Analysis Expressions (DAX) language\nT-SQL\nPower BI (Administration and Development)\nPower Query \u0026 M language\nPower Pivot\nAzure Data Lake\nAzure SQL Database\nAzure Data Factory\nAzure Data Bricks\nAzure Synapse (Serverless and/or Dedicated)\nAzure SQL Warehouse",
      "word_count": 66
    },
    {
      "bullet_count": 10,
      "heading": "Related Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "All of the following experience requirements",
        "last_5_words": "and opportunity management"
      },
      "text": "All of the following experience requirements involve active development of systems and solutions deployed to production environments.\n\nTechnical\n7+ years in BI Architecture, Data Warehousing, and Data Modeling\n5+ years of data- and BI-specific business analysis\n5+ years devoted to the Microsoft BI Stack (SSIS, SSAS, etc.)\n3+ years creating solutions in the Azure space using Lakehouse design patterns\n\nBusiness/Domain\nExperience in at least some of the following business data domains are expected given the listed technical experience above.\nFinance \u0026 Accounting\nGL, AR\nHuman Resources\nPayroll, Absence, Benefits\nProject Management\nCosts, revenue, planned vs. actual etc.\nProcure-to-Pay\nInvoice aging\nSales\nOpportunity management",
      "word_count": 155
    },
    {
      "bullet_count": 5,
      "heading": "Other Skills And Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Excellent English oral and written",
        "last_5_words": "work execution and team collaboration"
      },
      "text": "Excellent English oral and written communication skills\nBusiness analysis and requirements gathering techniques and practices\nFacility in managing stakeholder/SME relationships and building business partnerships\nAbility to collaborate effectively with technical and non-technical people, including those at the highest levels of the organization\nUses Agile software methodologies for work execution and team collaboration",
      "word_count": 56
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "BI"
    },
    {
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      "skill_name": "Data Warehousing"
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    },
    {
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      "skill_name": "Data Quality Management"
    },
    {
      "is_primary": true,
      "skill_name": "SQL Server"
    },
    {
      "is_primary": true,
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    },
    {
      "is_primary": true,
      "skill_name": "Tabular"
    },
    {
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      "skill_name": "SQL Server Integration Services"
    },
    {
      "is_primary": true,
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    },
    {
      "is_primary": true,
      "skill_name": "SQL Server Data Quality Services"
    },
    {
      "is_primary": true,
      "skill_name": "DAX"
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    {
      "is_primary": true,
      "skill_name": "T-SQL"
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    {
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    {
      "is_primary": true,
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    {
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      "skill_name": "Power Pivot"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Lake"
    },
    {
      "is_primary": true,
      "skill_name": "Azure SQL Database"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Factory"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Databricks"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Synapse"
    },
    {
      "is_primary": true,
      "skill_name": "Azure SQL Warehouse"
    },
    {
      "is_primary": true,
      "skill_name": "Lakehouse"
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    {
      "is_primary": true,
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    },
    {
      "is_primary": true,
      "skill_name": "Snowflake Schema"
    },
    {
      "is_primary": true,
      "skill_name": "Slowly Changing Dimension"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    }
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  "nano_parsed": {
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    "certifications": [],
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        "source_marker": {
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          "last_5_words": "and opportunity management"
        },
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        "bullet_count": 5,
        "heading": "Other Skills And Experience",
        "heading_was_present": true,
        "source_marker": {
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          "last_5_words": "work execution and team collaboration"
        },
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    "urls": []
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  "rejected": false,
  "rejection_reason": null,
  "run_id": "fd2cce53-d033-43a3-bbc1-06f0aa10f0de",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
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          },
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            "kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
            "sentence": "Data Quality Management: processes, patterns and practices for implementing a Data Quality Management strategy in the context of a BI strategy.",
            "similarity": 0.5961
          },
          {
            "kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
            "sentence": "Develops BI solutions in a team environment",
            "similarity": 0.5917
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.6084,
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        "total_count": null
      },
      {
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        "matched_count": null,
        "matched_skills": null,
        "role_id": 86,
        "score": 0.574,
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        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
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            "similarity": 0.5249
          },
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            "sentence": "Standard data warehousing processes, patterns and practices",
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        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 79,
        "score": 0.5356,
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        "total_count": null
      },
      {
        "display_name": "Scala Backend Developer",
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            "sentence": "Standard data warehousing processes, patterns and practices",
            "similarity": 0.4977
          },
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            "kra_text": "application data modeling",
            "sentence": "Design  Data prep patterns and practices",
            "similarity": 0.497
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 87,
        "score": 0.5321,
        "slug": "scala-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Node.js Backend Developer",
        "kra_matches": [
          {
            "kra_text": "data modeling and persistence access",
            "sentence": "Modern data modeling patterns and practices",
            "similarity": 0.6128
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            "sentence": "Dimensional data store schemas (star/snowflake)",
            "similarity": 0.4647
          },
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            "kra_text": "data modeling and persistence access",
            "sentence": "Standard data warehousing processes, patterns and practices",
            "similarity": 0.4547
          }
        ],
        "matched_count": null,
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        "role_id": 82,
        "score": 0.5107,
        "slug": "node-backend-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Power BI",
          "Star schema"
        ],
        "role_id": 2,
        "score": 0.0645,
        "slug": "data-engineer",
        "total_count": 31
      },
      {
        "display_name": "Python Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL Server"
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        "matched_count": 1,
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          "SQL Server"
        ],
        "role_id": 82,
        "score": 0.0323,
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      {
        "display_name": ".NET Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL Server"
        ],
        "role_id": 83,
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        "slug": "dotnet-backend-developer",
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        "display_name": "Kotlin Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL Server"
        ],
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        "score": 0.0323,
        "slug": "kotlin-server-backend-developer",
        "total_count": 31
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    ]
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  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "BI Developer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 147,
      "score": 0.97,
      "slug": "bi-developer",
      "total_count": null
    },
    "confidence": 0.97,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "BI solution architecture and development",
      "Data warehousing and data modeling",
      "Azure-based BI implementation",
      "BI strategy and technical advisory",
      "Data visualization and reporting",
      "Master data management and data quality"
    ],
    "matched_kras": [
      "Analyzes and designs BI solutions",
      "Develops BI solutions in a team environment",
      "Performs technology research, evaluation and selection",
      "Advises IT management on technical strategies",
      "Aligns BI solution designs to corporate and IT strategy",
      "Estimates project and solution costs",
      "Mentors developers on BI technology",
      "Design data prep patterns and practices",
      "Reliable batch data processing",
      "Data visualization patterns and practices"
    ],
    "matched_skills": [
      "BI solutions",
      "Microsoft BI stack",
      "SQL Server RDBMS",
      "SQL Server Analysis Services Tabular",
      "SQL Server Integration Services",
      "SQL Server Master Data Services",
      "SQL Server Data Quality Services",
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      "T-SQL",
      "Power BI",
      "Power Query",
      "Power Pivot",
      "Azure Data Lake",
      "Azure SQL Database",
      "Azure Data Factory"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on BI solution analysis/design, Microsoft BI stack development, Power BI/SSAS/SSIS work, and advising/mentoring on BI practices, which best matches BI Developer.",
    "sub_role": null
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  "stage5_updates": {
    "centroid_n_after": 12,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1865,
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      "role_slug": "bi-developer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 24353,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "BI",
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      },
      {
        "is_primary": true,
        "queue_id": 24354,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Data Warehousing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24355,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Data Modeling",
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      {
        "is_primary": true,
        "queue_id": 24356,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "ETL",
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      },
      {
        "is_primary": true,
        "queue_id": 24357,
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        "role_slug": "bi-developer",
        "skill_name": "Data Lake",
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      },
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        "is_primary": true,
        "queue_id": 24358,
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        "role_slug": "bi-developer",
        "skill_name": "Data Visualization",
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        "skill_name": "Master Data Management",
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        "role_slug": "bi-developer",
        "skill_name": "SQL Server Analysis Services",
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Tabular",
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      {
        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "SQL Server Master Data Services",
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        "is_primary": true,
        "queue_id": 24365,
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        "role_slug": "bi-developer",
        "skill_name": "SQL Server Data Quality Services",
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        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
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        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "T-SQL",
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        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Power Query",
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      },
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        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
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        "is_primary": true,
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        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Power Pivot",
        "status": "pending"
      },
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        "is_primary": true,
        "queue_id": 24371,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Azure Data Lake",
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      },
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        "is_primary": true,
        "queue_id": 24372,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Azure SQL Database",
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        "skill_name": "Azure Data Factory",
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      },
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        "is_primary": true,
        "queue_id": 24374,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Azure Databricks",
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      },
      {
        "is_primary": true,
        "queue_id": 24375,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Azure Synapse",
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      },
      {
        "is_primary": true,
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        "role_display_name": "BI Developer",
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        "skill_name": "Azure SQL Warehouse",
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      },
      {
        "is_primary": true,
        "queue_id": 24377,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Snowflake Schema",
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      },
      {
        "is_primary": true,
        "queue_id": 24378,
        "role_display_name": "BI Developer",
        "role_slug": "bi-developer",
        "skill_name": "Slowly Changing Dimension",
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    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
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    "v3_run_id": null
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}
API 2 — extract-details
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      "alias_persisted": false,
      "existing_alias_id": 5644,
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        "category_id": 8,
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        "id": 2379,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "domain-modeling",
        "sub_category_id": 2831,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2017,
      "existing_alias_text": "Data Lakes",
      "input_term": "Data Lake",
      "matched_canonical": {
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        "id": 1358,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "data-lakes",
        "sub_category_id": 1025,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 135,
      "existing_alias_text": "SQL Server",
      "input_term": "SQL Server",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "sql-server",
        "sub_category_id": 29,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 360,
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
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        "sub_category_id": 111,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 302,
      "existing_alias_text": "Azure Synapse Analytics",
      "input_term": "Azure Synapse",
      "matched_canonical": {
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        "display_name": "Azure Synapse Analytics",
        "id": 108,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "azure-synapse-analytics",
        "sub_category_id": 117,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2018,
      "existing_alias_text": "Lakehouse",
      "input_term": "Lakehouse",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "lakehouse",
        "sub_category_id": 1026,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 330,
      "existing_alias_text": "Star schema",
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      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
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        "sub_category_id": 70,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
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      "existing_alias_id": 332,
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 868,
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
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  ],
  "candidate_roles": [
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      "slug": "cloud-architect",
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      "display_name": "Data Engineer",
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    },
    {
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        "source": "db"
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    {
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      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Agile",
          "alias_type": "CANONICAL",
          "id": 868,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Agile",
        "id": 520,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Software Concepts, Patterns \u0026 Practices",
            "id": 478,
            "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
            "slug": "software-concepts-patterns-practices",
            "source": "db"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Agile",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "BI",
    "Data Warehousing",
    "ETL",
    "Data Visualization",
    "Master Data Management",
    "Data Quality Management",
    "SQL Server Analysis Services",
    "Tabular",
    "SQL Server Integration Services",
    "SQL Server Master Data Services",
    "SQL Server Data Quality Services",
    "DAX",
    "T-SQL",
    "Power Query",
    "M language",
    "Power Pivot",
    "Azure Data Lake",
    "Azure SQL Database",
    "Azure Data Factory",
    "Azure Databricks",
    "Azure SQL Warehouse",
    "Snowflake Schema"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "BI Developer",
    "id": 147,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on BI solution analysis/design, Microsoft BI stack development, Power BI/SSAS/SSIS work, and advising/mentoring on BI practices, which best matches BI Developer.",
    "role_archetype": null,
    "slug": "bi-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "BI",
      "tag": "new"
    },
    {
      "skill": "Data Warehousing",
      "tag": "new"
    },
    {
      "skill": "Data Modeling",
      "tag": "in_db"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Data Lake",
      "tag": "in_db"
    },
    {
      "skill": "Data Visualization",
      "tag": "new"
    },
    {
      "skill": "Master Data Management",
      "tag": "new"
    },
    {
      "skill": "Data Quality Management",
      "tag": "new"
    },
    {
      "skill": "SQL Server",
      "tag": "in_db"
    },
    {
      "skill": "SQL Server Analysis Services",
      "tag": "new"
    },
    {
      "skill": "Tabular",
      "tag": "new"
    },
    {
      "skill": "SQL Server Integration Services",
      "tag": "new"
    },
    {
      "skill": "SQL Server Master Data Services",
      "tag": "new"
    },
    {
      "skill": "SQL Server Data Quality Services",
      "tag": "new"
    },
    {
      "skill": "DAX",
      "tag": "new"
    },
    {
      "skill": "T-SQL",
      "tag": "new"
    },
    {
      "skill": "Power BI",
      "tag": "in_db"
    },
    {
      "skill": "Power Query",
      "tag": "new"
    },
    {
      "skill": "M language",
      "tag": "new"
    },
    {
      "skill": "Power Pivot",
      "tag": "new"
    },
    {
      "skill": "Azure Data Lake",
      "tag": "new"
    },
    {
      "skill": "Azure SQL Database",
      "tag": "new"
    },
    {
      "skill": "Azure Data Factory",
      "tag": "new"
    },
    {
      "skill": "Azure Databricks",
      "tag": "new"
    },
    {
      "skill": "Azure Synapse",
      "tag": "in_db"
    },
    {
      "skill": "Azure SQL Warehouse",
      "tag": "new"
    },
    {
      "skill": "Lakehouse",
      "tag": "in_db"
    },
    {
      "skill": "Star Schema",
      "tag": "in_db"
    },
    {
      "skill": "Snowflake Schema",
      "tag": "new"
    },
    {
      "skill": "Slowly Changing Dimension",
      "tag": "in_db"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    }
  ],
  "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": 147,
        "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": "Data 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": 147,
        "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": "Data 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": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Storage and Data Services",
          "id": 144,
          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
          "slug": "cloud-storage-and-data-services",
          "source": "db"
        },
        "dimension_id": 144,
        "input_skill": "Data Lake",
        "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": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 147,
        "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": "Data Lake",
        "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": [],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Relational Database Design",
          "id": 4,
          "rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
          "slug": "relational-database-design",
          "source": "db"
        },
        "dimension_id": 4,
        "input_skill": "SQL Server",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 18,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "BI and Visualization Tools",
          "id": 31,
          "rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
          "slug": "bi-and-visualization-tools",
          "source": "db"
        },
        "dimension_id": 31,
        "input_skill": "Power BI",
        "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": 151,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Data Warehouses",
          "id": 22,
          "rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
          "slug": "cloud-data-warehouses",
          "source": "db"
        },
        "dimension_id": 22,
        "input_skill": "Azure Synapse",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 147,
        "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": "Lakehouse",
        "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": 1359,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Modeling and Schema Design",
          "id": 26,
          "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
          "slug": "data-modeling-and-schema-design",
          "source": "db"
        },
        "dimension_id": 26,
        "input_skill": "Star Schema",
        "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": 126,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Modeling and Schema Design",
          "id": 26,
          "rationale": "Designing curated data structures for analytics and downstream consumption. Covers dimensional modeling, normalization tradeoffs, slowly changing dimensions, and schema evolution for durable datasets.",
          "slug": "data-modeling-and-schema-design",
          "source": "db"
        },
        "dimension_id": 26,
        "input_skill": "Slowly Changing Dimension",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 147,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Software Concepts, Patterns \u0026 Practices",
          "id": 478,
          "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
          "slug": "software-concepts-patterns-practices",
          "source": "db"
        },
        "dimension_id": 478,
        "input_skill": "Agile",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 6
  },
  "planner_output": null,
  "run_id": "fd2cce53-d033-43a3-bbc1-06f0aa10f0de"
}