Engineering Manager - Streaming

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

Engineering Manager for Databricks' Spark Structured Streaming team, focusing on building and enhancing stream processing capabilities within the Databricks Data Intelligence Platform. The role involves leading a team to improve engine architecture, state management, and performance for both open-source Spark and Databricks-specific components.

What you'd actually do

  1. Leading a talented engineering team in Spark™ Structured Streaming team developing and promoting the engine in OSS and the Databricks Data Intelligence Platform
  2. Overseeing sustained recruitment of top-tier talent, and upskilling talent on the team
  3. Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities
  4. Build software that is not just high quality but easy to operate.
  5. Make company wide impact by driving Stream Processing adoption across the Databricks product portfolio

Skills

Required

  • experience working in a related system, streaming, query processing, query optimization, including big-data ecosystem, Apache Spark™ or database internal
  • database systems
  • storage systems
  • distributed systems
  • language design
  • performance optimization
  • testing
  • quality
  • SLAs of a product
  • building and leading teams in a complex technical domain
  • attract, hire, and coach engineers
  • cross functional work with product management
  • understand product and customer personas

Nice to have

  • managing distributed teams preferred

What the JD emphasized

  • 5+ years experience working in a related system, streaming, query processing, query optimization, including big-data ecosystem, Apache Spark™ or database internal
  • Experience being responsible for testing, quality, and SLAs of a product.
  • Previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals