Engineering Manager - Streaming
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead engineers developing and promoting Apache Spark Structured Streaming across open source and the Databricks platform. You will recruit and upskill talent, execute product strategy, build operable high-quality software, drive stream-processing adoption, and manage technical debt and long-term architecture.
Requirements
- 5+ years of experience in systems, streaming, query processing, query optimization, big-data ecosystems, Apache Spark, or database internals
- Knowledge of database systems, storage systems, distributed systems, language design, or performance optimization
- Experience ensuring infrastructure-service quality, testing, and SLAs
- Experience building and leading teams in complex technical domains
- Experience hiring and coaching engineers
- Experience collaborating with product management and customers
Responsibilities
- Lead the Apache Spark Structured Streaming engineering team
- Develop and promote the streaming engine in open source and the Databricks platform
- Recruit and upskill engineering talent
- Execute product vision, strategy, and roadmap processes
- Build high-quality, operable software
- Drive stream-processing adoption across the product portfolio
- Manage technical debt and long-term architecture decisions