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Senior Staff Software Engineer - Lakeflow Pipelines Datasets

Databricks

Mountain View, California; San Francisco, California (San Francisco, California) Remote permanent

Posted: April 2, 2026

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Quick Summary

We are looking for a Senior Staff Software Engineer to join our Lakeflow Engineering team as a key member of our Declarative Dataflow Graphs, Materialized Views, Structured Streaming, and Flows team in Mountain View, California. The ideal candidate will have experience with building scalable data pipelines and working with large datasets. The successful candidate will be responsible for developing and deploying data processing workflows that meet the needs of our customers.

Job Description

Databricks builds the world's leading data and AI platform, used by tens of thousands of organizations to turn raw data into decisions that matter.

The Lakeflow Engineering team owns the entirety of the ETL product line: Declarative Dataflow Graphs, Materialized Views, Structured Streaming, and Flows. We run what is arguably the world's largest data engineering platform, processing exabytes of data daily across tens of thousands of customers. The problems we solve (fault-tolerant incremental computation, stream-batch unification, declarative pipeline orchestration at massive scale) sit at the frontier of what distributed data systems can do.

We're looking for a Senior Staff Engineer to serve as a technical architect and engineering leader for this platform. You'll own the long-term technical direction for how pipelines are defined, optimized, executed, and operated, shaping the systems that data teams worldwide depend on every day. You will work across one or more of the following areas to design and build the next generation of data infrastructure:

• Declarative Dataflow Processing

• Resource management

• Efficient storage structures

• Stream Processing and Complex Event Processing

• Autonomic Computing and Self-Managing Systems

The Impact you will have:

• Architect and deliver a highly scalable, fault-tolerant platform for declarative pipelines and materialized views serving thousands of production customers.

• Turn ambiguous, large-scale technical challenges into clear execution plans that ship incrementally and hold up at exabyte scale.

• Bridge the gap between research and production by bringing ideas from the academic literature or internal R&D into systems that solve real customer problems.

• Lead deep systems work: performance diagnosis on large production clusters, low-level debugging, and optimization that moves the needle on cost and latency.

• Shape product direction alongside engineering and product leadership, owning technical strategy from design through delivery.

• Drive complex, multi-team technical initiatives that require sustained coordination and clear technical judgment.

What We’re Looking For:

• 10+ years of experience building, operating, and evolving large-scale distributed systems in production.

• Deep expertise in one or more of: database internals, storage systems, distributed computing, streaming systems, language/API design, or performance engineering.

• Track record of executing against a multi-year technical vision through well-sequenced incremental milestones.

• Strong algorithmic foundations with the practical judgment to know when they matter and when simpler solutions win.

• A bias toward customer impact over technical novelty for its own sake.

• Experience building alignment across teams and driving initiatives from conception through customer adoption.

• BS, MS, or PhD in Computer Science or a related field (or equivalent depth of experience).

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range
$228,600—$314,250 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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