Description
We are seeking a dedicated Engineering Leader to spearhead Spark Structured Streaming development initiatives. Your primary mission will be to make Spark Structured Streaming state of the art Stream Processing engine by adding advanced features such as sophisticated state management, new operators and making the engine performance both from latency and throughput point of view by reimagining engine architecture.
Key responsibilities include:
- Leading a talented engineering team in Spark Structured Streaming team developing and promoting the engine in OSS and the Databricks Data Intelligence Platform
- Overseeing sustained recruitment of top-tier talent, and upskilling talent on the team
- Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organisational goals and priorities
- Build software that is not just high quality but easy to operate
- Make company wide impact by driving Stream Processing adoption across the Databricks product portfolio
- Manage technical debt, including long term technical architecture decisions and balance product roadmap
What we look for:
- 5+ years experience working in a related system, streaming, query processing, query optimisation, including big-data ecosystem, Apache Spark or database internal
- A passion for database systems, storage systems, distributed systems, language design, or performance optimisation
- Can ensure the team builds high quality and reliable infrastructure services. 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
- Ability to attract, hire, and coach engineers who meet the Databricks hiring standards. Can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members. Can gain trust of the team and guide their careers
- Comfortable working cross functionally with product management and directly with customers; ability to deeply understand product and customer personas
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.