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
Atlassian Austin, Texas, USA Office
Atlassian believes the future of work is distributed and offers our people the flexibility to help them do what’s important to them. And with few exceptions, we hire people anywhere we have a legal entity as long as they have eligible work rights and sufficient team time zone overlap.
Atlassian Austin, Texas, USA Office
303 Colorado St , Austin, TX, United States, 78701
Similar Jobs at Atlassian
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Provides organization-wide technical leadership for Atlassian’s Dev AI platforms and autonomous developer initiatives. Defines multi-year architectures for agent runtimes, orchestration engines, execution sandboxes, memory systems, and context retrieval. Drives distributed-system architecture, reliability, security, responsible AI governance, evaluation, and operational standards. Leads cross-organizational technical initiatives, resolves architectural ambiguity, mentors senior engineers, partners with product and engineering leaders, and remains hands-on with strategic prototypes and architectural validation.
Top Skills:
Agent OrchestrationAi Evaluation FrameworksArtificial IntelligenceAtlassian Teamwork GraphAutonomous Ai AgentsBitbucketCode IntelligenceCode SynthesisDistributed SystemsJIRAResponsible AiRetrieval SystemsRuntime SandboxesSemantic SearchTelemetry
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Principal Software Engineer responsible for owning customer-facing products end to end, leading technical strategy, architecting large-scale distributed systems, and delivering AI-native experiences. The role involves full-stack implementation, product strategy, system design, code reviews, reliability, testing, telemetry, security, performance, and mentoring engineers. Candidates must have extensive experience building and operating large-scale systems and strong product, UX, communication, and collaboration skills.
Top Skills:
Automated TestingDistributed SystemsProduction Telemetry
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Serve as a pre-sales product expert for Atlassian enterprise sales. Partner with account teams and channel partners to discover customer needs, map business problems to Atlassian solutions, identify expansion opportunities, lead customized demonstrations, guide technical evaluations, and build customer buy-in. Collaborate with sales counterparts, track customer and competitive feedback, advocate for product improvements, and continuously develop solution and sales-process expertise.
Top Skills:
Atlassian Software
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
