Engineering Manager

At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions.

Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world.

The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies, timely & accurate metering & billing, cost optimization tools, intelligent resource usage controls, and cutting-edge engineering. As an Engineering Manager in Money
, you will be key to one of Databricks’ most central engineering orgs
. You will own critical components that form the backbone of our business, working closely with infrastructure as well as product teams in bringing critical monetization functionality to Databricks customers.

• Hire great engineers to build an outstanding team and support their career development by providing clear and timely feedback.
• Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).
• Work with engineering and product leadership to build a long-term roadmap
  .
• Coordinate execution and collaborate across teams to successfully deliver cross-cutting strategic projects
  .

• 10+ years of extensive experience with large-scale distributed systems alongside processes around testing, monitoring, SLAs etc
• 5+ years of engineering management experience
  , building, managing and mentoring high-performing software engineering teams
• Demonstrated success in collaborating with multiple cross-functional stakeholders to align system features and architecture, to deliver impactful platform projects.
• Experience in developing and implementing proactive mechanisms for failure detection and incident prevention.
• Excellent leadership, communication, and project management skills.
• BS (or higher) in Computer Science, or a related field.

Pay Range Transparency

Local Pay Range

$181,300 — $241,075 USD

About Databricks

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, Linked In and Facebook.

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, please visit

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.