Qualifications
Responsibilities
Benefits
Responsibilities
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.
CompensationAt 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 go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay RangesIn The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $238,500 - $311,375
Zone B: $214,650 - $280,238
Zone C: $197,955 - $258,441
Qualifications15+ years of experience in data engineering, data platform, or data management, with a focus on data strategy, architecture, governance, and platform buildout
8+ years of experience leading data engineering teams, including leading senior and principal-level architects and landing architecture through teams outside your reporting line
Demonstrated experience standing up or scaling an enterprise data catalog or metadata platform — DataHub, Unity Catalog, or equivalent — owning integration, adoption, and outcome metrics rather than tool administration
Demonstrated experience owning a data governance operating model end to end: policy, domain ownership, stewardship, classification, data quality, and controls that held up under 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 intended for machine consumption, including agent-facing metadata access such as MCP servers, semantic search endpoints, or context APIs
Experience across both corporate data domains (Finance, People, GTM) and customer or product data, with judgment about how their risk profiles differ
Working fluency in privacy and regulatory requirements — GDPR, CCPA/CPRA, SOX, SOC 2 — and practical command of classification schemes, access control models (RBAC/ABAC), masking, tokenization, and purpose limitation
Technical depth to lead a design review with a principal engineer: strong SQL, modern lakehouse platforms (Snowflake, Databricks, BigQuery), transformation tooling such as dbt, orchestration, and streaming/CDC patterns
Experience implementing DevOps best practices within the data platform, including CI/CD, data observability, monitoring, and lineage
Experience building services and RESTful APIs, and exposing metadata or platform capability programmatically for machine consumption
Demonstrated experience developing influential relationships and trust with senior leaders across different departments, and driving voluntary adoption from data producers who do not report to you
Prior experience partnering with Analytics, Data Science, Engineering, Security, Privacy, Legal and Product Management teams
A graduate degree in Computer Science, Information Management or a similar subject area
It's great but not required if you have:
Experience applying LLMs to governance work itself — metadata and description generation, classification, entity resolution, or data quality anomaly triage
Experience working for SaaS companies, including multi-tenant customer data, tenant isolation, and data residency at scale
Experience with responsible AI programs or AI governance frameworks such as the NIST AI RMF, ISO/IEC 42001, or the EU AI Act
DAMA-DMBOK grounding, CDMP, or a privacy certification such as CIPP or CIPT
Committed code to open source projects
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
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