Engineering Manager, Data Lineage - Unity Catalog Experience
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Job Description
RDQ426R207
About the Role
Databricks is seeking an experienced Engineering Manager to lead the development of Data Lineage as a first-class platform feature within Unity Catalog. This role will drive strategic efforts to enhance our data governance, discovery, and impact analysis capabilities-foundational pillars for our customers' data management and trust in Databricks.
As part of the Unity Catalog Experience team, you will lead a talented team of engineers, collaborate cross-functionally with product and platform teams, and help expand the scale and usability of lineage across the Databricks ecosystem.
Why This Role Matters
Data Lineage is one of the most critical components of Unity Catalog. It underpins the effectiveness of enterprise data governance and insights. By building lineage as a scalable, integrated platform capability, you will:
- Enable enterprise-grade data governance through proactive impact analysis and change management
- Empower data discovery with rich metadata and data flow visualization
- Facilitate problem identification and root-cause analysis across the data platform
- Provide context-aware lineage across the UI and programmatic interfaces
- Improve data documentation and transparency for both internal and external users
- Integrate with third-party catalogs, supporting bi-directional lineage exchange with partners like Atlan, Alation, Collibra, and Purview
- Influence intelligent features such as alerting, insights, and automated suggestions using lineage metadata
Key Responsibilities:
Team Leadership & Strategy
Manage, mentor, and grow a high-performing engineering team
Define the long-term vision for Data Lineage at Databricks in collaboration with Product and Design
Drive execution across complex technical domains while maintaining high engineering quality
Technical Ownership
Lead the architecture and implementation of scalable lineage systems that integrate seamlessly with Unity Catalog
Ensure lineage metadata is consistent, accurate, and consumable across Databricks products
Partner with internal platform teams and cloud storage integrations (AWS, Azure, GCP)
Cross-Functional Collaboration
Work closely with teams across data governance, metadata management, and catalog ingestion
Collaborate with partner ecosystem teams to enable lineage integrations with third-party catalog tools
Use Case Expansion
Extend lineage coverage to support new use cases such as:
Impact analysis for governance teams
Embedded lineage for data scientists and analysts
Documentation automation and audit readiness