Engineering Manager - Streaming

Overview

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 the Spark™ Structured Streaming team responsible for building Stream Processing capabilities into Spark™ and the 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 a best‑in‑class managed offering for customers to run their Stream Processing workloads.

• Lead a talented engineering team in the Spark™ Structured Streaming team, developing and promoting the engine in OSS and the Databricks Data Intelligence Platform.
• Oversee sustained recruitment of top‑tier talent and up‑skill talent on the team.
• Implement robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational 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.

• 5+ years of experience working in a related system, including big‑data ecosystem, Apache Spark™ or database internals.
• A passion for database systems, storage systems, distributed systems, language design, or performance optimization.
• Ability to ensure the team builds high‑quality and reliable infrastructure services. Experience 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 upscale the existing team through hiring top‑notch senior talent, growing leaders, and helping struggling members.
• Experience managing distributed teams preferred.
• Comfortable working cross‑functionally with product management and directly with customers; ability to deeply understand product and customer personas.

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.

Local Pay Range: $181,000 – $241,000 USD.

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.

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit

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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