Data Governance Analyst Senior

Intermountain Health•Lake Park, IA
•$44 - $70•Hybrid

About The Position

The Senior Data Governance Analyst is responsible for designing, developing, and implementing processes related to metadata management, reference data management and data quality monitoring. This position is expected to have hands-on experience with the technical solution selected for the Data Governance program and good understanding of Data Governance principles and processes. This role will directly report to the Data Governance Manager, performing analysis on a variety of routine to moderately complex projects under general supervision and typically leading moderately complex initiatives or projects. We are committed to offering flexible work options where approved and stated in the job posting. However, we are currently not considering candidates who reside or plan to reside in the following states: California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Minnesota, New York, Pennsylvania, Rhode Island, Virginia, Vermont, Washington. Please note that a video interview through Microsoft Teams will be required as well as potential onsite interviews and meetings.

Requirements

  • Experience in performing key Data Governance work such as data cataloging, data lineage, data classification, reference data management, and business glossary management
  • Experience with system and data integration via API
  • Experience with major Electronic Health Record (EHR) vended solutions and deep understanding of the backend data architecture and data modeling
  • Advanced SQL skills and proficient knowledge about database design, ETL processes and data mapping
  • Experience with data quality monitoring data quality improvement
  • Experience as a “team player” and the ability to work effectively with colleagues across and at all levels within the organization
  • Proficiency in PowerPoint, Excel, Word, etc. and effective verbal, written and interpersonal communication skills

Nice To Haves

  • Bachelor’s or Master's degree in IT or analytics related fields. Degree must be obtained through an accredited institution. Education or experience is verified
  • Experience in an analyst or engineer role working with data governance technologies and processes
  • Certification or training in data governance or related areas (e.g., DMBoK, CDMP, etc.)
  • Demonstrated experience developing conceptual, semantic, or data models that represent complex business concepts, relationships, hierarchies, and business rules.
  • Proven ability to analyze and disambiguate complex business terminology and translate business requirements into computable definitions, taxonomies, ontologies, or semantic models that support AI initiatives.
  • Experience facilitating cross-functional stakeholder discussions to establish shared business meaning, standard definitions, and enterprise-wide information models

Responsibilities

  • Develop conceptual and semantic models for enterprise business domains, including entities, concepts, relationships, hierarchies, taxonomies, and business rules that support operational, analytical, and AI use cases.
  • Analyze and resolve ambiguous or conflicting business terminology by facilitating discussions with stakeholders to establish precise, consistent, and reusable business definitions.
  • Translate business concepts into computable semantic structures that can be implemented within MDM, analytics, data catalogs, semantic layers, knowledge graphs, and AI-enabled solutions.
  • Partner with business owners, stewards, architects, and engineering teams to align conceptual models with logical and physical data models while preserving business intent and meaning.
  • Establish and maintain enterprise business glossaries, ontologies, taxonomies, and reference-data structures that promote consistency across systems and domains.
  • Identify authoritative sources, ownership boundaries, survivorship rules, and semantic relationships for critical business data assets.
  • Conduct domain discovery and business architecture analysis to understand business processes, capabilities, lifecycles, decision points, and information requirements.
  • Support master data management initiatives by defining business concepts, relationships, and governance requirements that guide MDM design and implementation.
  • Define semantic requirements for AI, knowledge-graph, semantic-layer, and agent-enabled solutions, ensuring that enterprise meaning can be consumed consistently by both humans and AI systems.
  • Develop modeling standards, governance practices, and documentation to ensure semantic assets are governed, reusable, auditable, and maintained over time.

Benefits

  • generous benefits package that covers a wide range of programs to foster a sustainable culture of wellness that encompasses living healthy, happy, secure, connected, and engaged.
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