Head of Data Governance & Enterprise Context Eng

Atlassian; United States; Remote; USD 239,000 - 311,000; Full time

Job summary

Atlassian is seeking an Engineering Leader to own data governance and the enterprise context that makes our data trusted and AI-ready. You will manage the governance model, domain ownership, and the steward network, aligning policy with Privacy, Legal, Security, and Compliance while driving data quality as a product.

You will also define and execute the technical strategy for the data catalog, metadata, and lineage platforms, connecting business entities to ownership and quality signals, exposed

Qualifications

• 15+ years of experience in data engineering, data platform, or data management with governance focus.
• 8+ years leading data engineering teams, including senior/principal architects.
• Experience scaling an enterprise data catalog or metadata platform with adoption metrics.
• Proven data governance operating model ownership across policy, stewardship, and quality.
• Data-as-a-product mindset with data contracts and governance as code.

Responsibilities

• Own the enterprise data governance operating model, domain ownership, and stewardship networks.
• Shape architecture for data catalog, metadata, and lineage platforms across the company.
• Define AI readiness and gate data used by models and agents via contracts and classifications.
• Drive adoption of governance practices across federated teams in Legal, Privacy, Security, and Compliance.

Skills

Data governance

Data architecture

Data contracts

SQL

Lakehouse

dbt

CI/CD

Data quality

Stakeholder mgmt

RBAC/ABAC

Privacy compliance

Semantic layer

Metadata catalog

REST APIs

Leadership

Education

Graduate degree in Computer Science or Information Management

Tools

Snowflake

Databricks

BigQuery

DataHub

Unity Catalog

DBT

Job description

Overview

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.

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.

Compensation

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 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 Ranges

In 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

Qualifications

• 15+ 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 it