Engineering Manager - Streaming
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
We are “Spark Structured Streaming” team responsible for building Stream Processing capabilities into Spark and Databricks Intelligence Platform. Stream processing is in its infancy and we are here to build not just state-of-the-art Stream Processing technology, but best in class managed offering for customers to run their Stream Processing workloads.
We're seeking a dedicated Engineering Leader to spearhead Spark Structured Streaming development initiatives, encompassing both open source and Databricks-specific components. 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 at the same time making the engine performance both from latency and throughput point of view by reimagining engine architecture.
You will report directly to the Senior Manager of Engineering.
The main responsibilities include:
- You will lead a talented engineering team in Spark Structured Streaming team developing and promoting the engine in OSS and the Databricks Data Intelligence Platform.
- You will oversee sustained recruitment of top-tier talent, and upskilling talent on the team.
- You will build processes to implement product vision and strategy, according to organizational goals and priorities.
- You will build software that is not just high quality but easy to operate.
- You will make a company wide impact by guiding Stream Processing adoption across the Databricks product portfolio.
- You will 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, including big-data ecosystem, Apache Spark or database internal
- A passion for database systems, storage systems, distributed systems, language design, or performance optimization
- Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and Service Level Agreements of a product. Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals.
- Expertise attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Can up level the existing team via hiring top-notch senior talent, growing leaders and helping struggling members. Experience managing distributed teams.
- Experience working with product management, and directly with customers; ability to understand customer needs.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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. For more information regarding which range your location is in visit our page here.
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
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