Senior Data Governance Analyst (with AI Enablement) | W2 Only | Remote.

Xlysi•Dallas, TX

17h•Remote

About The Position

This role focuses on Data Governance and Quality, with a strong emphasis on AI Enablement. The Senior Data Governance Analyst will be responsible for establishing and maintaining data governance practices, ensuring data quality, and leveraging semantic architecture, ontologies, and knowledge graphs. The position requires hands-on experience with data catalog tools, proficiency in SQL and Snowflake, and a strong ability to collaborate with business partners. Experience in the healthcare industry is highly preferred, as is familiarity with modern knowledge management techniques and AI-assisted tools for documentation and analysis.

Requirements

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.
Proficiency in SQL and Snowflake.
Hands-on experience with data catalog tools (specifically Coalesce catalog side).
Strong communication skills.
Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery.
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.
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.
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.
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.

Nice To Haves

Master Data Management (MDM) experience is highly preferred/desired.
Experience with Agile methodology is a plus (trainable if lacking).
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 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.
Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.

Responsibilities

Establish and maintain data governance practices.
Ensure data validation and data quality assurance.
Work with semantic layers, ontologies, and knowledge graphs.
Utilize data catalog tools, specifically Coalesce catalog.
Collaborate directly with business partners.
Support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
Translate technical data structures into clear, business-aligned definitions and documentation.
Perform data profiling, validation, reconciliation, and issue investigation using SQL.
Work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
Manage multiple priorities in an Agile environment.
Identify opportunities to improve governance workflows, data usability, automation, AI-assisted documentation, and scalable self-service analytics.