Job description

P-1110 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 Lakeflow Engineering team, responsible for Databricks ETL product line such as Spark Declarative Pipelines, Structured Streaming, and Ingestion. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers. We're seeking a dedicated Engineering Leader to spearhead the Materialized Views engineering team. The team is responsible for building next generation Materialized View features for both ETL workloads and for query acceleration. The main responsibilities include: You will lead an engineering team building the next-generation Materialized View features for the Databricks Lakeflow 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. What we look for: Minimum 3 years of experience in managing top-tier engineering teams 5+ years experience building data infrastructure systems such as Apache Spark™ or database internals. A passion for database systems, storage systems, distributed systems, or performance optimization Experience working with product management, and directly with customers; ability to understand customer needs. 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 in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members. 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. For more information regarding which range your location is in visit our page here . Local Pay Range $228,600 — $317,233 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits 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 click here . 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. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Requirements

Must-haves

You will lead an engineering team building the next-generation Materialized View features for the Databricks Lakeflow 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.
Minimum 3 years of experience in managing top-tier engineering teams
5+ years experience building data infrastructure systems such as Apache Spark™ or database internals.
A passion for database systems, storage systems, distributed systems, or performance optimization
Experience working with product management, and directly with customers; ability to understand customer needs.
Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.
Our Commitment to Diversity and Inclusion

Nice-to-haves

None flagged.

Application prep

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Platform: greenhouse
Effort: quick

Benefits

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