Senior Staff Software Engineer - Lakeflow Pipelines Datasets

Databricks Databricks · Data AI · San Francisco, CA · Executive Engineering - Pipeline

Senior Staff Engineer to architect and lead the long-term technical direction for Databricks' Lakeflow ETL product line, focusing on declarative dataflow graphs, materialized views, structured streaming, and flows. This role involves designing and building next-generation data infrastructure for massive-scale distributed systems.

What you'd actually do

  1. Architect and deliver a highly scalable, fault-tolerant platform for declarative pipelines and materialized views serving thousands of production customers.
  2. Turn ambiguous, large-scale technical challenges into clear execution plans that ship incrementally and hold up at exabyte scale.
  3. 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.
  4. Lead deep systems work: performance diagnosis on large production clusters, low-level debugging, and optimization that moves the needle on cost and latency.
  5. Shape product direction alongside engineering and product leadership, owning technical strategy from design through delivery.

Skills

Required

  • 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).

What the JD emphasized

  • large-scale distributed systems
  • exabyte scale
  • multi-year technical vision