Data Governance Lead
Listed on 2026-03-05
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IT/Tech
Data Analyst
Job Title
Data Governance Lead
LocationFranklin, TN
About OMNIA PartnersOMNIA Partners has become the largest and most experienced purchasing organization for public and private sector markets by delivering unparalleled scale and solutions. Through further organic growth and strategic acquisitions, OMNIA Partners will continue to drive economies of scale to execute more contracts, in more verticals, with transparent, value-driven pricing for our membership of companies. Our success and growth have been unparalleled in this space.
At the core of our success is a high energy, talented staff with diverse skills and a unified focus on delivering value and an emphasis on creativity, strategic thinking, and execution.
AboutThe Role
The Data Governance Lead is a strategic, hands‑on leader responsible for establishing and maturing OMNIA Partners’ enterprise data governance and master data management (MDM) program from the ground up. This role defines and drives the frameworks, policies, operating model, and practices that ensure our data is trusted, well‑defined, and consistently used to create business value across the organization.
Partnering closely with a third‑party data governance and MDM implementation partner, technology teams, and business stakeholders, this role will design and stand up the governance framework, launch core processes, and then scale the operating model by hiring and leading a network of data stewards over time. The Data Governance Lead serves as the primary liaison and advocate for data governance and MDM across business units and senior leadership, connecting strategy to execution and embedding governance into everyday workflows.
WhatYou’ll Do Data governance strategy and operating model
- Oversee, define, and execute a multi‑year data governance and master data management strategy and roadmap that aligns with OMNIA Partners’ objectives and broader data transformation initiatives.
- Stand up an enterprise data governance framework, including charters, decision‑making forums, and RACI for key roles (executive sponsors, data owners, data stewards, custodians).
- Set a practical, implementable approach to rollout of stewardship across business units, phasing adoption in line with readiness and value.
- Define and operationalize data leadership/ownership, stewardship, and accountability across all critical data domains (e.g., Member, Supplier, Product, Financial).
- Establish and lead the Data Governance working group and any leadership steering forums, facilitating decision‑making on data standards, policies, priorities, and critical data issues.
- Serve as the primary liaison and advocate for data governance and MDM across business units and senior leadership, clearly articulating the business value of data quality, alignment, and consistent definitions.
- Develop, implement, and enforce data policies, standards, and procedures for data lifecycle management, quality, sharing, and usage, ensuring they are practical and adoptable.
- Design and implement core data governance controls such as data classification, access, retention, and usage guidelines, partnering with Security, Privacy, Legal, and Compliance where needed.
- Collaborate with Data Stewards, Business Stakeholders, Data Leaders/Owners, and internal team members to define data quality rules and implement monitoring and remediation processes.
- Establish and report Key Data Quality Indicators (KDQIs) and metrics (e.g., accuracy, completeness, consistency, timeliness), leveraging them to drive continuous improvement.
- Direct the development and execution of the master data management and alignment strategy, including implementation and ongoing evolution.
- Define and govern master data definitions, rules, and hierarchies to achieve a “single source of truth” for critical data elements across domains.
- Oversee data integration and synchronization processes to ensure consistent master data across operational and analytical systems.
- Create a comprehensive playbook for embedding stewardship practices into the implementation of MDM functionality and the semantic layer in Snowflake.
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