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Data Governance Lead

Job in Omaha, Douglas County, Nebraska, 68197, USA
Listing for: HDR
Full Time position
Listed on 2026-05-17
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Data Scientist, Data Security
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we weave diversity, equity, and inclusion into our work and foster a sense of belonging throughout the company and within our communities, we constantly ask ourselves:
What is our impact on the world?

Watch Our Story:

Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.

Data Governance Lead

The Data Governance Lead drives enterprise-wide consistency in how HDR defines, documents, governs, and uses data—so teams can trust what they see, reuse data confidently, and scale analytics and AI. This role partners with the Technology Office and a distributed network of Data Stewards to keep shared definitions, data products, and data classifications current, accessible, and actionable.

Why This Role Matters

Across HDR, teams rely on data every day to plan work, deliver projects, answer questions, and make decisions. When data is defined differently from team to team, project to project, or region to region, it becomes harder to trust, reuse, and scale. This role reduces time spent reconciling definitions, rebuilding datasets, and clarifying what something really means—so employees can use data with confidence.

HDR is investing in enterprise data platforms and AI-enabled tools. The value of these investments comes not only from technology, but from the quality, consistency, and clear ownership of the data inside them.

Without clear, ongoing data ownership, teams face inconsistent definitions, duplicated effort, and slower decision-making.

By partnering with approximately 100 Data Stewards, this role ensures shared data definitions are documented, easy to find, and consistently understood. The result is less confusion, less rework, and more time spent using data to move work forward.

Impact:
Project teams spend less time cleaning, duplicating, or re-explaining data and more time delivering work. Leaders get faster access to reliable information and greater trust in the insights used to guide decisions.

At an enterprise level, this role strengthens data readiness for analytics, automation, and AI by driving consistency, documentation, and active ownership.

What You’ll Achieve
  • Employees can access a single “Data Storefront” to find consistent glossary definitions, understand available data products (certified reports, HDR-curated datasets, and approved external datasets), and follow clear access request processes.
  • Employees can use AI chat with greater confidence because inputs leverage approved business glossary definitions, data classifications, and curated/approved datasets.
  • Data Stewards understand what data they own, how it is used, and what decisions they are accountable for.
Key Responsibilities
  • Develop and maintain a listing of Data Stewards and Data Owners across corporate data domains and Business Classes.
  • Administer and evolve the Business Glossary in the Data Catalog—ensuring definitions reflect real business usage, link to the correct steward and approval process, and resolving definition/ownership conflicts.
  • Develop and maintain the Data Products Catalog —ensuring each product is clearly described, has documented access/usage requirements, and is linked to the correct owner and approval process.
  • Lead alignment between Data Stewards and the Data Science team to define, document, and sustain data classifications that enable analytics, AI modeling, and future automation.
  • Facilitate Data Steward practice groups to share patterns and ideas, address recurring issues, and prevent one-off governance decisions.
  • Contribute to the development of enterprise data quality frameworks; ensure discrepancies are reported, followed up, and resolved in collaboration with the Technology team responsible for administering the framework.
  • Refresh governance guidance as tools or regulations change.
  • Own and execute annual hard…
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