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Apply to Senior Data Governance Analyst (with AI Enablement) | W2 Only (No OPT's please).
Core Competencies & Technical Skills:
Data Governance & Quality: Strong background in data governance practices, data validation, and data quality assurance.
Semantic Architecture: Practical experience with semantic layers, ontologies, and knowledge graphs.
Data Cataloging: Hands-on experience with data catalog tools (specifically Coalesce catalog side).
Technical Stack: Proficient in SQL and Snowflake.
Master Data Management (MDM): MDM experience is highly preferred/desired.
Soft Skills & Business Acumen:
Strong communication skills with a proven ability to collaborate directly with business partners.
Experience with Agile methodology is a plus (trainable if lacking).
Detailed JD:
Your qualifications
· Bachelor's degree in information systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field; equivalent experience may be considered.
· 3+ years of experience in data engineering, data governance, data management, data quality, analytics, business intelligence, metadata management, knowledge management, or related data-focused role.
· Experience in the health care industry, especially in areas such as Medicare Advantage, clinical analytics, medical economics, quality, pharmacy, claims, provider, member, or operational data environments, is strongly preferred.
· Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery preferred.
· Familiarity with modern warehouse and open Lakehouse concepts, including cloud object storage, open table formats such as Apache Iceberg or Delta Lake, metadata catalogs, data sharing, lineage, and governance of structured and semi-structured data.
· Familiarity with using AI-assisted tools to improve documentation, analysis, data discovery, metadata quality, and governance workflows.
· Experience with enterprise data catalog, metadata management, data lineage, business glossary, stewardship, and/or or report certification practices.
· Experience with BI and reporting platforms such as Power BI, Tableau, SSRS, or similar tools.
· Experience with CLI tools such as Cortex Code, Claude Code, or similar.
· Experience working in SAFe Agile or another Agile delivery framework.
· Preferred certifications include CDMP, DGSP, DCAM, DAMA-related training, Snowflake certification, Microsoft Power BI certification, or relevant Agile/SAFe certifications.
Competencies
· Knowledge Management Mindset: Helps organize business meaning, definitions, relationships, ownership, and metadata so that enterprise data is easier to find, understand, govern, and reuse.
· Business Partnership: Builds trusted relationships with business and technical stakeholders and translates governance, data quality, and AI-readiness practices into business value.
· Analytical Thinking: Uses structured analysis to evaluate data issues, identify root causes, assess business impact, and improve trust in data used for analytics and AI-enabled capabilities.
· Governance Discipline: Applies consistent standards for definitions, metadata, quality rules, stewardship, lineage, and documentation.
· Communication: Explains complex data concepts clearly to both technical and non-technical audiences.
· Continuous Improvement: Identifies opportunities to improve governance workflows, data usability, automation, AI-assisted documentation and scalable self-service analytics.
Skills & Abilities
· Ability to support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
· Familiarity with knowledge management concepts such as ontologies, knowledge graphs, taxonomies, and domain models.
· Ability to translate technical data structures into clear, business-aligned definitions and documentation, especially via data dictionaries, catalog entries, report inventories, data quality findings, and usage context.
· Strong SQL skills for data profiling, validation, reconciliation, and issue investigation.
· Familiarity with Snowflake, Alteryx, SQL Server, Power BI, Tableau, SSRS, data catalogs, modern analytics platforms, and open lakehouse concepts such as cloud object storage, open table formats, metadata catalogs, and governed data access.
· Ability to work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
· Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.
· Ability to manage multiple priorities in an Agile environment while maintaining attention to detail.
· Awareness of emerging automation, AI-assisted documentation, data quality monitoring, semantic search, and governed by self-service analytics capabilities.
Data Governance & Quality: Strong background in data governance practices, data validation, and data quality assurance.
Semantic Architecture: Practical experience with semantic layers, ontologies, and knowledge graphs.
Data Cataloging: Hands-on experience with data catalog tools (specifically Coalesce catalog side).
Technical Stack: Proficient in SQL and Snowflake.
Master Data Management (MDM): MDM experience is highly preferred/desired.
Soft Skills & Business Acumen:
Strong communication skills with a proven ability to collaborate directly with business partners.
Experience with Agile methodology is a plus (trainable if lacking).
Detailed JD:
Your qualifications
· Bachelor's degree in information systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field; equivalent experience may be considered.
· 3+ years of experience in data engineering, data governance, data management, data quality, analytics, business intelligence, metadata management, knowledge management, or related data-focused role.
· Experience in the health care industry, especially in areas such as Medicare Advantage, clinical analytics, medical economics, quality, pharmacy, claims, provider, member, or operational data environments, is strongly preferred.
· Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery preferred.
· Familiarity with modern warehouse and open Lakehouse concepts, including cloud object storage, open table formats such as Apache Iceberg or Delta Lake, metadata catalogs, data sharing, lineage, and governance of structured and semi-structured data.
· Familiarity with using AI-assisted tools to improve documentation, analysis, data discovery, metadata quality, and governance workflows.
· Experience with enterprise data catalog, metadata management, data lineage, business glossary, stewardship, and/or or report certification practices.
· Experience with BI and reporting platforms such as Power BI, Tableau, SSRS, or similar tools.
· Experience with CLI tools such as Cortex Code, Claude Code, or similar.
· Experience working in SAFe Agile or another Agile delivery framework.
· Preferred certifications include CDMP, DGSP, DCAM, DAMA-related training, Snowflake certification, Microsoft Power BI certification, or relevant Agile/SAFe certifications.
Competencies
· Knowledge Management Mindset: Helps organize business meaning, definitions, relationships, ownership, and metadata so that enterprise data is easier to find, understand, govern, and reuse.
· Business Partnership: Builds trusted relationships with business and technical stakeholders and translates governance, data quality, and AI-readiness practices into business value.
· Analytical Thinking: Uses structured analysis to evaluate data issues, identify root causes, assess business impact, and improve trust in data used for analytics and AI-enabled capabilities.
· Governance Discipline: Applies consistent standards for definitions, metadata, quality rules, stewardship, lineage, and documentation.
· Communication: Explains complex data concepts clearly to both technical and non-technical audiences.
· Continuous Improvement: Identifies opportunities to improve governance workflows, data usability, automation, AI-assisted documentation and scalable self-service analytics.
Skills & Abilities
· Ability to support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
· Familiarity with knowledge management concepts such as ontologies, knowledge graphs, taxonomies, and domain models.
· Ability to translate technical data structures into clear, business-aligned definitions and documentation, especially via data dictionaries, catalog entries, report inventories, data quality findings, and usage context.
· Strong SQL skills for data profiling, validation, reconciliation, and issue investigation.
· Familiarity with Snowflake, Alteryx, SQL Server, Power BI, Tableau, SSRS, data catalogs, modern analytics platforms, and open lakehouse concepts such as cloud object storage, open table formats, metadata catalogs, and governed data access.
· Ability to work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
· Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.
· Ability to manage multiple priorities in an Agile environment while maintaining attention to detail.
· Awareness of emerging automation, AI-assisted documentation, data quality monitoring, semantic search, and governed by self-service analytics capabilities.