Head of Data Governance & Enterprise Context Engineering

About the role

Atlassian is looking for an Engineering Leader to join its Data Engineering team and own data governance and the enterprise context that makes its data trusted and AI-ready. The role owns the enterprise data governance operating model and shapes the technical strategy and architecture of the data catalog, metadata and lineage platform, with a remote option available.

Key responsibilities

• Own the enterprise data governance operating model: domain ownership, decision rights, the governance council and the steward network
• Set policy for classification, access, retention and acceptable use with Privacy, Legal, Security and Compliance, and run data quality as a product
• Shape the technical strategy and architecture of the data catalog, metadata and lineage platform, and build enterprise context connecting business entities to ownership, lineage and quality signals, exposed programmatically for agents and applications
• Shift governance left into data contracts, automated classification at ingest and policy-as-code, and define AI readiness as a certifiable state that gates what data models and agents can use
• Drive adoption of these practices across a federated organization

Required profile

• 15+ years in data engineering, data platform or data management, focused on strategy, architecture, governance and platform buildout
• 8+ years leading data engineering teams, including senior and principal architects, and landing architecture through teams outside your reporting line
• Demonstrated experience scaling an enterprise data catalog or metadata platform (DataHub, Unity Catalog or equivalent)
• End-to-end ownership of a data governance operating model that stood up to audit or regulatory scrutiny
• Experience with a data-as-a-product or data contracts operating model
• Experience building a semantic layer, ontology or knowledge graph for machine consumption, including agent-facing metadata access
• Experience across corporate data domains (Finance, People, GTM) and customer or product data
• Fluency in privacy and regulatory requirements (GDPR, CCPA/CPRA, SOX, SOC 2) and classification, access control, masking and tokenization
• Graduate degree in Computer Science, Information Management or a similar field

Required skills

• Strong SQL and modern lakehouse platforms (Snowflake, Databricks, BigQuery)
• dbt, orchestration and streaming/CDC patterns
• CI/CD, data observability, monitoring and lineage
• Building services and RESTful APIs, exposing metadata programmatically
• Building trust with senior leaders and driving voluntary adoption from data producers

Nice to have: applying LLMs to governance work, SaaS experience, responsible AI frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act), DAMA-DMBOK, CDMP or a privacy certification, and open source contributions. Base pay ranges from $197,955 to $311,375 depending on location; benefits, bonuses, commissions and equity may also apply.