Pipeline run
a8064634-85e4-4674-8be7-aa73e82c2350
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
The roles and responsibilities of Technical Manager/Senior Technical Manager - Database will include the below: Ø Partners with clients to understand their business and create comprehensive business r…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
SQL Server / MySQL DBA
domain · Database Specialists CASE DOMAINslug: sql-server-mysql-dba · id: 198 · source: db
Domain=Database Specialists; The JD centers on SQL Server, databases, BI/reporting, data warehouse, and cloud data platforms, which best matches the SQL Server / MySQL DBA family despite the managerial scope.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Description - “Technical Manager/ Senior Technical Manager - Database” Company Profile Merilytics, an Accordion company is a fast-growing, analytics firm offering advanced and intelligent analytical solutions to clients globally. We combine domain expertise, advanced analytics and technology to provide robust solutions for clients’ business problems. You can find further details about the company at https://merilytics.com. We partner with our clients in Private Equity, CPG, Retail, Healthcare, Media & Entertainment, Technology, Logistics industries etc. by providing analytical solutions to generate superior returns. We solve clients’ business problems by analyzing large amount of data to help guide their Operations, Marketing, Pricing, Customer Strategies, and much more. Position Merilytics, an Accordion company is looking for Technical Manager/Senior Technical Manager - Database. He/she will be responsible for the design, development, configuration/deployment, and maintenance of the above technology stack. He/she must have in-depth understanding of various tools & technologies in the above domain to design and implement robust and scalable solutions which address client current and future requirements at optimal costs. The Technical Manager should be able to evaluate existing architectures and recommend way to upgrade and improve the performance of architectures – both on-premises and cloud-based solutions. A successful Technical Manager should possess strong working business knowledge, familiarity with multiple tools and techniques along with industry standards and best practices in Business Intelligence and Data Warehousing environment. He/she should have strong organizational, critical thinking, and communication skills. Location: Hyderabad Roles and Responsibilities The roles and responsibilities of Technical Manager/Senior Technical Manager - Database will include the below: Ø Partners with clients to understand their business and create comprehensive business requirements. Ø Develop end-to-end Business Intelligence framework based on requirements including recommending appropriate architecture (on-premises or cloud-based), analytics and reporting. Ø Work closely with the business and technology teams to guide in solution development and implementation. Ø Work closely with the business teams to arrive at methodologies to develop KPIs and Metrics. Ø Work with Project Manager in developing and executing project plans within assigned schedule and timeline. Ø Develop standard reports and functional dashboards based on business requirements. Ø Conduct training programs and knowledge transfer sessions to junior developers when needed. Recommend improvements to provide optimum reporting solutions. Ø Curiosity to learn new tools and technologies to provide futuristic solutions for clients. Pre-requisites and skillsets required to apply for this role: Ø Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred. Ø More than 7 years of experience in related field Ø Proven expertise in SQL Server (SSIS, SSAS and SSRS) Ø In-depth knowledge of databases (SQL Server, MySQL, Oracle etc.) and data warehouse (any one of Azure Synapse, AWS Redshift, Google BigQuery, Snowflake etc.) Ø In-depth knowledge of business intelligence tools (any one of Power BI, Tableau, Qlik, DOMO, Looker etc.) Ø Good understanding of either Azure (OR) AWS: Ø Azure (Data Factory & Pipelines, SQL Database & Managed Instances, DevOps, Logic Apps, Analysis Services) OR Ø AWS (Glue, Redshift, RDS, QuickSight etc.) Ø Proven abilities to take on initiative and be innovative. Ø Analytical mind with problem solving attitude. Why Explore a Career at Merilytics: Ø High growth environment: Semi-annual performance management and promotion cycles coupled with a strong meritocratic culture, enables fast track to leadership responsibility. Ø Cross Domain Exposure: Interesting and challenging work streams across industries and domains that always keep you excited, motivated, and on your toes. Ø Entrepreneurial Environment: Intellectual freedom to make decisions and own them. We expect you to spread your wings and assume larger responsibilities. Ø Fun culture and peer group: Non-bureaucratic and fun working environment; Strong peer environment that will challenge you and accelerate your learning curve. Ø Other benefits for full time employees: o Health and wellness programs that include employee health insurance covering immediate family members and parents, term life insurance for employees, free health camps for employees, discounted health services (including vision, dental) for employee and family members, free doctor’s consultations, counsellors, etc o Corporate Meal card options for ease of use and tax benefits o Work dinners, team lunches, company sponsored team outings and celebrations. o Reimbursement support for travel to office, as and when promulgated by the Company. o Cab reimbursement for women employees beyond a certain time of the day o Robust leave policy to support work-life balance. Specially designed leave structure to support woman employees for maternity and related requests. o Reward and recognition platform to celebrate professional and personal milestones. o A positive & transparent work environment including various employee engagement and employee benefit initiatives to support personal and professional learning and development.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
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)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- MySQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- Oracle Corporation
- License
- gpl_v2
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: MySQL appears in a large share of backend/DB job descriptions and remains a standard managed offering across AWS RDS, Cloud SQL, and Azure Database, indicating broad hiring-pipeline demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Data Modeling Catalog dimension db id 216
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Relational Database Usage Catalog dimension db id 371
Library dimension (catalog)
Roles linked in library: Go Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Synapse Analytics (CANONICAL) primary
Context tags (catalog)
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
|
Aliases — catalog
- Amazon Redshift (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Data Warehouse Service
- Vendor
- Amazon Web Services
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly listed in data/analytics job descriptions and widely used as AWS’s managed warehouse; strong vendor adoption and steady JD volume signal broad market demand.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 118
- 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
|
Aliases — catalog
- BigQuery (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Data Warehouse Service
- Vendor
- License
- proprietary
- Year introduced
- 2011
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: BigQuery appears frequently in data/analytics job descriptions and is a core Google Cloud warehouse offering, with broad enterprise adoption and strong ecosystem support.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 118
- 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
|
Aliases — catalog
- Snowflake (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Cloud Platform
- Vendor
- Snowflake Inc.
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Snowflake appears frequently in data/analytics job postings and is a standard cloud data warehouse platform alongside BigQuery and Redshift.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 113
- 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
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Power BI (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- Tableau (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Tableau Software
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Business Intelligence Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Business Intelligence Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Looker (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Google Cloud
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Looker appears frequently in BI/analytics job descriptions and is a standard enterprise analytics platform, especially after Google Cloud’s acquisition expanded market visibility.
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) |
Aliases — catalog
- Azure (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2010
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
-
Vendor Product Families Catalog dimension db id 477
Library dimension (catalog)
Roles linked in library: Engineering Manager
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- AWS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Amazon
- License
- other_open
- Year introduced
- 2006
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
-
Vendor Product Families Catalog dimension db id 477
Library dimension (catalog)
Roles linked in library: Engineering Manager
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Devops Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2018
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure DevOps appears in many enterprise job descriptions for CI/CD, boards, and repos, and Microsoft continues active product support and updates; it remains a common hiring-pipeline skill alongside GitHub Actions/Jenkins.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 170
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Integration Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- AWS RDS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Managed Relational Database Service
- Vendor
- Amazon Web Services
- License
- proprietary
- Year introduced
- 2009
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS RDS is broadly listed in cloud/backend job descriptions and is a standard managed database service in AWS stacks; it remains actively offered by AWS with no sunset signal.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 2845
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms & Hosting Providers Catalog dimension db id 278
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Business Intelligence Tools
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| SQL Server | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure Synapse | new |
Cloud Data Warehouses
cloud-data-warehouses
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| AWS Redshift | new |
Cloud Data Warehouses
cloud-data-warehouses
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Google BigQuery | new |
Cloud Data Warehouses
cloud-data-warehouses
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Snowflake | in_db |
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | — | 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) | |
| Tableau | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Looker | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Amazon RDS | new |
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | SSIS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SSAS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SSRS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Oracle | type=Databases subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Qlik | type=Business Intelligence Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | DOMO | type=Business Intelligence Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure Data Factory | type=Data Engineering Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Pipelines | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure SQL Database | type=Databases subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure SQL Managed Instance | type=Databases subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Logic Apps | type=Integration Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure Analysis Services | type=Data Engineering Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | AWS Glue | type=Data Engineering Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Amazon QuickSight | type=Business Intelligence Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Azure Synapse ↔ Cloud Data Warehouses | |
| dimension_skill_link_proposed | AWS Redshift ↔ Cloud Data Warehouses | |
| dimension_skill_link_proposed | Google BigQuery ↔ Cloud Data Warehouses | |
| dimension_skill_link_proposed | Amazon RDS ↔ Cloud Platforms & Hosting Providers |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Merilytics, an Accordion company is",
"last_5_words": "Pricing, Customer Strategies, and much more."
},
"text": "Merilytics, an Accordion company is a fast-growing, analytics firm offering advanced and intelligent analytical solutions to clients globally. We combine domain expertise, advanced analytics and technology to provide robust solutions for clients\u2019 business problems. We partner with our clients in Private Equity, CPG, Retail, Healthcare, Media \u0026 Entertainment, Technology, Logistics industries etc. by providing analytical solutions to generate superior returns. We solve clients\u2019 business problems by analyzing large amount of data to help guide their Operations, Marketing, Pricing, Customer Strategies, and much more.",
"word_count": 84
},
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"SQL Server",
"Snowflake",
"Tableau",
"Power BI",
"Looker",
"BigQuery",
"AWS",
"metrics",
"dashboards",
"Make",
"DevOps",
"Redshift",
"RDS",
"Analytics",
"Azure",
"MySQL",
"Cloud",
"sessions",
"Role",
"SQL",
"Streams",
"Location",
"roles"
],
"certifications": [],
"company_name": "Merilytics",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Analytics Firm",
"Business Intelligence"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Any Discipline",
"raw": "Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred.",
"requirement": "preferred"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "More than 7 years of experience in related field"
},
"job_locations": [
{
"aliases": [
"Hyderabad, AP"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Technical Manager/Senior Technical Manager - Database",
"role_aliases": [
"Technical Manager",
"Senior Technical Manager",
"Database Manager"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 8,
"heading": "Roles and Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The roles and responsibilities of",
"last_5_words": "futuristic solutions for clients."
},
"text": "The roles and responsibilities of Technical Manager/Senior Technical Manager - Database will include the below:\n\u00d8 Partners with clients to understand their business and create comprehensive business requirements.\n\u00d8 Develop end-to-end Business Intelligence framework based on requirements including recommending appropriate architecture (on-premises or cloud-based), analytics and reporting.\n\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.\n\u00d8 Work closely with the business teams to arrive at methodologies to develop KPIs and Metrics.\n\u00d8 Work with Project Manager in developing and executing project plans within assigned schedule and timeline.\n\u00d8 Develop standard reports and functional dashboards based on business requirements.\n\u00d8 Conduct training programs and knowledge transfer sessions to junior developers when needed. Recommend improvements to provide optimum reporting solutions.\n\u00d8 Curiosity to learn new tools and technologies to provide futuristic solutions for clients.",
"word_count": 134
},
{
"bullet_count": 8,
"heading": "Pre-requisites and skillsets required to apply for this role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u00d8 Undergraduate degree (B.E/B.Tech.) from",
"last_5_words": "problem solving attitude."
},
"text": "\u00d8 Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred.\n\u00d8 More than 7 years of experience in related field\n\u00d8 Proven expertise in SQL Server (SSIS, SSAS and SSRS)\n\u00d8 In-depth knowledge of databases (SQL Server, MySQL, Oracle etc.) and data warehouse (any one of Azure Synapse, AWS Redshift, Google BigQuery, Snowflake etc.)\n\u00d8 In-depth knowledge of business intelligence tools (any one of Power BI, Tableau, Qlik, DOMO, Looker etc.)\n\u00d8 Good understanding of either Azure (OR) AWS:\n\u00d8 Azure (Data Factory \u0026 Pipelines, SQL Database \u0026 Managed Instances, DevOps, Logic Apps, Analysis Services) OR\n\u00d8 AWS (Glue, Redshift, RDS, QuickSight etc.)\n\u00d8 Proven abilities to take on initiative and be innovative.\n\u00d8 Analytical mind with problem solving attitude.",
"word_count": 139
}
],
"urls": [
{
"type": "website",
"url": "https://merilytics.com"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "SQL Server"
},
{
"is_primary": true,
"skill_name": "SSIS"
},
{
"is_primary": true,
"skill_name": "SSAS"
},
{
"is_primary": true,
"skill_name": "SSRS"
},
{
"is_primary": true,
"skill_name": "MySQL"
},
{
"is_primary": true,
"skill_name": "Oracle"
},
{
"is_primary": true,
"skill_name": "Azure Synapse"
},
{
"is_primary": true,
"skill_name": "AWS Redshift"
},
{
"is_primary": true,
"skill_name": "Google BigQuery"
},
{
"is_primary": true,
"skill_name": "Snowflake"
},
{
"is_primary": true,
"skill_name": "Power BI"
},
{
"is_primary": true,
"skill_name": "Tableau"
},
{
"is_primary": true,
"skill_name": "Qlik"
},
{
"is_primary": true,
"skill_name": "DOMO"
},
{
"is_primary": true,
"skill_name": "Looker"
},
{
"is_primary": true,
"skill_name": "Azure"
},
{
"is_primary": true,
"skill_name": "AWS"
},
{
"is_primary": true,
"skill_name": "Azure Data Factory"
},
{
"is_primary": true,
"skill_name": "Pipelines"
},
{
"is_primary": true,
"skill_name": "Azure SQL Database"
},
{
"is_primary": true,
"skill_name": "Azure SQL Managed Instance"
},
{
"is_primary": true,
"skill_name": "Azure DevOps"
},
{
"is_primary": true,
"skill_name": "Logic Apps"
},
{
"is_primary": true,
"skill_name": "Azure Analysis Services"
},
{
"is_primary": true,
"skill_name": "AWS Glue"
},
{
"is_primary": true,
"skill_name": "Amazon RDS"
},
{
"is_primary": true,
"skill_name": "Amazon QuickSight"
}
],
"jd_role": {
"display_name": "Technical Manager/Senior Technical Manager - Database",
"rationale": null,
"role_aliases": [
"Technical Manager",
"Senior Technical Manager",
"Database Manager"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Merilytics, an Accordion company is",
"last_5_words": "Pricing, Customer Strategies, and much more."
},
"text": "Merilytics, an Accordion company is a fast-growing, analytics firm offering advanced and intelligent analytical solutions to clients globally. We combine domain expertise, advanced analytics and technology to provide robust solutions for clients\u2019 business problems. We partner with our clients in Private Equity, CPG, Retail, Healthcare, Media \u0026 Entertainment, Technology, Logistics industries etc. by providing analytical solutions to generate superior returns. We solve clients\u2019 business problems by analyzing large amount of data to help guide their Operations, Marketing, Pricing, Customer Strategies, and much more.",
"word_count": 84
},
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"SQL Server",
"Snowflake",
"Tableau",
"Power BI",
"Looker",
"BigQuery",
"AWS",
"metrics",
"dashboards",
"Make",
"DevOps",
"Redshift",
"RDS",
"Analytics",
"Azure",
"MySQL",
"Cloud",
"sessions",
"Role",
"SQL",
"Streams",
"Location",
"roles"
],
"certifications": [],
"company_name": "Merilytics",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Analytics Firm",
"Business Intelligence"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Any Discipline",
"raw": "Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred.",
"requirement": "preferred"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "More than 7 years of experience in related field"
},
"job_locations": [
{
"aliases": [
"Hyderabad, AP"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Technical Manager/Senior Technical Manager - Database",
"role_aliases": [
"Technical Manager",
"Senior Technical Manager",
"Database Manager"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 8,
"heading": "Roles and Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The roles and responsibilities of",
"last_5_words": "futuristic solutions for clients."
},
"text": "The roles and responsibilities of Technical Manager/Senior Technical Manager - Database will include the below:\n\u00d8 Partners with clients to understand their business and create comprehensive business requirements.\n\u00d8 Develop end-to-end Business Intelligence framework based on requirements including recommending appropriate architecture (on-premises or cloud-based), analytics and reporting.\n\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.\n\u00d8 Work closely with the business teams to arrive at methodologies to develop KPIs and Metrics.\n\u00d8 Work with Project Manager in developing and executing project plans within assigned schedule and timeline.\n\u00d8 Develop standard reports and functional dashboards based on business requirements.\n\u00d8 Conduct training programs and knowledge transfer sessions to junior developers when needed. Recommend improvements to provide optimum reporting solutions.\n\u00d8 Curiosity to learn new tools and technologies to provide futuristic solutions for clients.",
"word_count": 134
},
{
"bullet_count": 8,
"heading": "Pre-requisites and skillsets required to apply for this role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u00d8 Undergraduate degree (B.E/B.Tech.) from",
"last_5_words": "problem solving attitude."
},
"text": "\u00d8 Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred.\n\u00d8 More than 7 years of experience in related field\n\u00d8 Proven expertise in SQL Server (SSIS, SSAS and SSRS)\n\u00d8 In-depth knowledge of databases (SQL Server, MySQL, Oracle etc.) and data warehouse (any one of Azure Synapse, AWS Redshift, Google BigQuery, Snowflake etc.)\n\u00d8 In-depth knowledge of business intelligence tools (any one of Power BI, Tableau, Qlik, DOMO, Looker etc.)\n\u00d8 Good understanding of either Azure (OR) AWS:\n\u00d8 Azure (Data Factory \u0026 Pipelines, SQL Database \u0026 Managed Instances, DevOps, Logic Apps, Analysis Services) OR\n\u00d8 AWS (Glue, Redshift, RDS, QuickSight etc.)\n\u00d8 Proven abilities to take on initiative and be innovative.\n\u00d8 Analytical mind with problem solving attitude.",
"word_count": 139
}
],
"urls": [
{
"type": "website",
"url": "https://merilytics.com"
}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "a8064634-85e4-4674-8be7-aa73e82c2350",
"stage3_signals": {
"alias_found": false,
"alias_match_roles": [],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"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": "\u00d8 Develop end-to-end Business Intelligence framework based on requirements including recommending appropriate architecture (on-premises or cloud-based), analytics and reporting.",
"similarity": 0.5398
},
{
"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": "\u00d8 Develop standard reports and functional dashboards based on business requirements.",
"similarity": 0.5055
},
{
"kra_text": "Optimizes pipeline throughput, partitioning strategies, and query performance across cloud data warehouses like Snowflake, BigQuery, or Redshift.",
"sentence": "\u00d8 In-depth knowledge of databases (SQL Server, MySQL, Oracle etc. ) and data warehouse (any one of Azure Synapse, AWS Redshift, Google BigQuery, Snowflake etc. )",
"similarity": 0.5048
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5167,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "\u00d8 In-depth knowledge of databases (SQL Server, MySQL, Oracle etc. ) and data warehouse (any one of Azure Synapse, AWS Redshift, Google BigQuery, Snowflake etc. )",
"similarity": 0.5252
},
{
"kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
"sentence": "\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.",
"similarity": 0.5189
},
{
"kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
"sentence": "\u00d8 Partners with clients to understand their business and create comprehensive business requirements.",
"similarity": 0.4465
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.4968,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "\u00d8 Good understanding of either Azure (OR) AWS:",
"similarity": 0.5031
},
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "The roles and responsibilities of Technical Manager/Senior Technical Manager - Database will include the below:",
"similarity": 0.4639
},
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.",
"similarity": 0.4493
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.4721,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": "Engineering Manager",
"kra_matches": [
{
"kra_text": "Set team goals and delivery plans",
"sentence": "\u00d8 Work with Project Manager in developing and executing project plans within assigned schedule and timeline.",
"similarity": 0.5014
},
{
"kra_text": "facilitate technical and delivery decisions",
"sentence": "\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.",
"similarity": 0.4572
},
{
"kra_text": "Set team goals and delivery plans",
"sentence": "\u00d8 Work closely with the business teams to arrive at methodologies to develop KPIs and Metrics.",
"similarity": 0.427
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 121,
"score": 0.4618,
"slug": "engineering-manager",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Provisions and manages cloud infrastructure on AWS, Azure, or GCP using Terraform or CloudFormation to enforce infrastructure-as-code standards.",
"sentence": "\u00d8 Good understanding of either Azure (OR) AWS:",
"similarity": 0.4997
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "\u00d8 Conduct training programs and knowledge transfer sessions to junior developers when needed.",
"similarity": 0.4445
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "\u00d8 Work closely with the business and technology teams to guide in solution development and implementation.",
"similarity": 0.4402
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.4615,
"slug": "devops-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 6,
"matched_skills": [
"AWS",
"Azure",
"Looker",
"Power BI",
"Snowflake",
"Tableau"
],
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}
}
API 2 — extract-details
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{
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"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
}
],
"input_skill": "Amazon RDS",
"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": [],
"canonical": null,
"dimensions": [],
"input_skill": "Amazon QuickSight",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Business Intelligence Tools",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "amazon-quicksight",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"SSIS",
"SSAS",
"SSRS",
"Oracle",
"Qlik",
"DOMO",
"Azure Data Factory",
"Pipelines",
"Azure SQL Database",
"Azure SQL Managed Instance",
"Logic Apps",
"Azure Analysis Services",
"AWS Glue",
"Amazon QuickSight"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "SQL Server / MySQL DBA",
"id": 198,
"rationale": "Domain=Database Specialists; The JD centers on SQL Server, databases, BI/reporting, data warehouse, and cloud data platforms, which best matches the SQL Server / MySQL DBA family despite the managerial scope.",
"role_archetype": null,
"slug": "sql-server-mysql-dba",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "SQL Server",
"tag": "in_db"
},
{
"skill": "SSIS",
"tag": "new"
},
{
"skill": "SSAS",
"tag": "new"
},
{
"skill": "SSRS",
"tag": "new"
},
{
"skill": "MySQL",
"tag": "in_db"
},
{
"skill": "Oracle",
"tag": "new"
},
{
"skill": "Azure Synapse",
"tag": "in_db"
},
{
"skill": "AWS Redshift",
"tag": "in_db"
},
{
"skill": "Google BigQuery",
"tag": "in_db"
},
{
"skill": "Snowflake",
"tag": "in_db"
},
{
"skill": "Power BI",
"tag": "in_db"
},
{
"skill": "Tableau",
"tag": "in_db"
},
{
"skill": "Qlik",
"tag": "new"
},
{
"skill": "DOMO",
"tag": "new"
},
{
"skill": "Looker",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Azure Data Factory",
"tag": "new"
},
{
"skill": "Pipelines",
"tag": "new"
},
{
"skill": "Azure SQL Database",
"tag": "new"
},
{
"skill": "Azure SQL Managed Instance",
"tag": "new"
},
{
"skill": "Azure DevOps",
"tag": "in_db"
},
{
"skill": "Logic Apps",
"tag": "new"
},
{
"skill": "Azure Analysis Services",
"tag": "new"
},
{
"skill": "AWS Glue",
"tag": "new"
},
{
"skill": "Amazon RDS",
"tag": "in_db"
},
{
"skill": "Amazon QuickSight",
"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": 198,
"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": 198,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"dimension_id": 216,
"input_skill": "MySQL",
"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": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"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": "MySQL",
"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": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"dimension_id": 371,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"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": 198,
"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": "AWS Redshift",
"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": 198,
"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": "Google BigQuery",
"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": 198,
"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": "Snowflake",
"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": 105,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"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": 198,
"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": "Tableau",
"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": 150,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"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": "Looker",
"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": 152,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "Azure",
"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": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms \u0026 Managed Services",
"id": 221,
"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
"slug": "cloud-platforms-managed-services",
"source": "db"
},
"dimension_id": 221,
"input_skill": "Azure",
"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": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms for AI Deployment",
"id": 211,
"rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
"slug": "cloud-platforms-for-ai-deployment",
"source": "db"
},
"dimension_id": 211,
"input_skill": "Azure",
"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,
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"source": "db"
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],
"skill_dimension_saved": true,
"skill_id": 188,
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},
{
"chosen_role_id": 198,
"dimension": {
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"source": "db"
},
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"role_dimension_saved": false,
"roles_from_db": [
{
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{
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"source": "db"
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],
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{
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},
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"roles_from_db": [
{
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{
"display_name": "Cyber Security Engineer",
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"slug": "cybersecurity-engineer",
"source": "db"
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],
"skill_dimension_saved": true,
"skill_id": 188,
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{
"chosen_role_id": 198,
"dimension": {
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"display_name": "Vendor Product Families",
"id": 477,
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"source": "db"
},
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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": [
{
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}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
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{
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"dimension": {
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
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"source": "db"
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{
"display_name": "Cyber Security Engineer",
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{
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"source": "db"
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{
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{
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{
"display_name": "Go Backend Developer",
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"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
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"slug": "java-backend-developer",
"source": "db"
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{
"display_name": "Kotlin Backend Developer",
"id": 84,
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"source": "db"
},
{
"display_name": "ML Engineer",
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"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
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"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
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"role_archetype": "Engineering",
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"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
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"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 187,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 198,
"dimension": {
"difficulty_hint": "well_known",
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"id": 211,
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"source": "db"
},
"dimension_id": 211,
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
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"slug": "ai-engineer",
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}
],
"skill_dimension_saved": true,
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"skill_tag": "in_db",
"skipped_reason": null
},
{
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},
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"roles_from_db": [
{
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},
{
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}
],
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},
{
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},
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{
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{
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}
],
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},
{
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"display_name": "Vendor Product Families",
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},
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{
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],
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{
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},
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{
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],
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},
{
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"dimension": {
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"display_name": "Cloud Platforms \u0026 Hosting Providers",
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"rationale": "Familiarity with vendor-specific hosting and backend services for deploying and scaling web applications.",
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"source": "db"
},
"dimension_id": 278,
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"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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{
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{
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{
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{
"display_name": "Web Developer",
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}
],
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],
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},
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.