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# Senior Staff Software Engineer - Lakeflow Pipelines Datasets

- **Company:** Databricks
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $314,250.0
- **Contract:** Permanent contract
- **Skills:** Databases, Data Infrastructure, Software Debugging, Distributed Systems, Fault Tolerance, Data Flow Control, Information Technology, Complex Event Processing, Api Design, Stream Processing
- **Published:** October 26, 2026
- **Apply:** https://www.adzuna.com/details/5696483151

## About the Role

* 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).

## Description

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.