Leads Atlassian’s enterprise data governance operating model and trusted, AI-ready data strategy. Owns governance policies, domain ownership, decision rights, stewardship, data quality, catalog, metadata, lineage, and enterprise context architecture. Partners with Privacy, Legal, Security, and Compliance while implementing data contracts, automated classification, policy-as-code, and certification controls. Drives governance adoption across a federated organization and enables agents and applications to consume reliable, governed data.
Analytics & Data Science | San Francisco, United States | Remote, Remote | Seattle, United States
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Data is a big deal at Atlassian. We ingest billions of events each month into our analytical platforms, and dozens of teams across the company depend on that data to run the business. As AI systems increasingly consume our data alongside our teams, the standard has risen: data must be clearly described, accurately classified, explicitly owned, and demonstrably trustworthy before it can be put to use
Atlassian is looking for an Engineering Leader to join the Data Engineering team and own data governance and the enterprise context that makes our data trusted and AI-ready.
You will own the enterprise data governance operating model - domain ownership, decision rights, the governance council, and the steward network - setting policy for classification, access, retention, and acceptable use with Privacy, Legal, Security, and Compliance, and running data quality as a product . In parallel, you will shape the technical strategy and architecture for our data catalog, metadata, and lineage platform, and build the enterprise context that connects business entities to their ownership, lineage, and quality signals - exposed programmatically so that agents and applications consume trusted context . You will shift governance left into data contracts, automated classification at ingest, and policy-as-code, define AI readiness as a certifiable state that continuously gates what data our models and agents can use, drive adoption across a federated organization.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Data is a big deal at Atlassian. We ingest billions of events each month into our analytical platforms, and dozens of teams across the company depend on that data to run the business. As AI systems increasingly consume our data alongside our teams, the standard has risen: data must be clearly described, accurately classified, explicitly owned, and demonstrably trustworthy before it can be put to use
Atlassian is looking for an Engineering Leader to join the Data Engineering team and own data governance and the enterprise context that makes our data trusted and AI-ready.
You will own the enterprise data governance operating model - domain ownership, decision rights, the governance council, and the steward network - setting policy for classification, access, retention, and acceptable use with Privacy, Legal, Security, and Compliance, and running data quality as a product . In parallel, you will shape the technical strategy and architecture for our data catalog, metadata, and lineage platform, and build the enterprise context that connects business entities to their ownership, lineage, and quality signals - exposed programmatically so that agents and applications consume trusted context . You will shift governance left into data contracts, automated classification at ingest, and policy-as-code, define AI readiness as a certifiable state that continuously gates what data our models and agents can use, drive adoption across a federated organization.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
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