About the role
Please Note: This is a Utah-based hybrid position which will require some regular in-office days each week. Additionally, employment with BambooHR is contingent on passing both a background and credit check. AI at BambooHR At BambooHR, we’re all about setting people free to do great work, and we believe AI is a powerful partner in that mission. We’re leaning into intelligent tools to streamline our workflows, giving us more time for high-impact innovation. We look for curious, forward-thinking people who are ready to explore how AI can elevate their work and help us reimagine the future of HR. Essential Job Duties At BambooHR, we’re building a world where data helps people do their best work. As we continue to grow our data platform and AI capabilities, we’re looking for a Senior Data Governance Engineer to help ensure our data is trusted, well-defined, and ready to power better decisions across the company. If you enjoy solving messy data problems, bringing clarity to complexity, and helping teams use data the right way—this role is for you. You’ll be a key part of our Data Governance team, helping us scale how we manage, define, and use data across BambooHR. You will: Make Data More Trusted Identify and help resolve data quality issues across systems Facilitate change control reviews to protect key data pathways Analyze and validate data to ensure it’s accurate, complete, and consistent Build AI agents to certified data assets Help Define “One Version of the Truth” Partner with teams across the business to define and document key metrics and KPIs Support our data certification efforts so teams can rely on consistent, trusted data Help align reporting, dashboards, and semantic models to shared definitions Improve Data Discoverability Contribute to our data catalog and KPI library hosted in Open MetaData Assist in the administration of data asset management tools and systems Document data definitions, lineage, and ownership Add context and annotations to make data easier to find, understand, and unlock AI use cases Support Data Governance Across the Company Work with data stewards, business leaders, and technical teams to apply governance standards Help scale governance practices across departments through data committees Partner with Legal and InfoSec to ensure proper handling and protection of PII and sensitive data Manage relationships with business, product, and engineering data owners Partner with enterprise application owners to drive improvements to data sources, ensuring more accurate and reliable data Help Govern AI & Data-Powered Experiences Support governance for AI-driven tools like data assistants, copilots, and agentic AI Help ensure AI systems use the right data, in the right way, with proper controls Contribute to processes that make AI outputs more transparent, traceable, and trustworthy Partner with platform and AI teams to align on responsible data usage What Success Looks Like Teams trust the data they’re using to make decisions Key metrics are clearly defined and consistently used Data is easier to find, understand, and use across the company Data quality issues are identified and resolved quickly AI-powered tools connect seamlessly with trusted data sources with proper guardrails What You Need to Get the Job Done 5+ years of experience in data governance, data analytics, or related roles Strong SQL skills and experience working directly with data Experience improving data quality and working with large datasets Familiarity with data platforms (data warehouse, lakehouse, etc.) Familiarity with common enterprise applications and associated data domains Understanding of how metrics, reporting, and self-service analytics work Ability to communicate clearly and collaborate across teams B.S./M.S. in Computer Science, Information Systems, Business Analytics or related field What Will Make Us REALLY Love You Experience with data governance tools (i.e. Open Metadata, Collibra, Atlan, Informatica) Familiarity with Databricks, DBT, Snowflake, Claude code, Codex, Windsurfer Experience with data lineage, observability, or data quality tools Exposure to AI/ML systems or data products powered by AI Knowledge of data privacy and compliance
