Engineering Manager - Distributed Data Systems

Engineering Manager - Distributed Data Systems

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. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The impact you will have:

• Recruit a world-class software engineering team, from sourcing to closing.
• Drive strategic vision for the team and product.
• Establish high technical standards through processes and culture.
• Mentor and coach engineers to help them carve out a fulfilling career.
• Deliver infrastructure and product to make our customers' lives better, and to support Databricks' record-breaking growth.
• Evangelize and uphold our cultural principles: be customer obsessed, be data-driven, team work makes the dream work, and own it.
• Hire great engineers to build an outstanding team.
  • Support engineers in their career development by providing clear feedback and develop engineering leaders.
  • 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 unblock cross-cutting projects.

What we look for:

• BS or higher in Computer Science, or a related field
• At least two years of experience building and leading highly complex, technical engineering teams.
• Motivated by delivering customer value and impact.
• Ability to attract, hire, and coach world-class engineers.
• Experience with distributed systems, databases, compilers, performance optimisation or big data systems (Spark, Hadoop)
• Comfortable working cross functionality with product management and directly with customers; ability to deeply understand product and customer personas.
• Experience managing, hiring and coaching software engineering teams.
  • Experience with large-scale distributed web services and the processes around testing, monitoring, and SLAs to ensure high product quality.
  • Experience managing an ML platform, SaaS, or data focused product.
  • Work with partners in other departments (PM, Sales, CS) to improve outcomes.
  • BS (or higher) in Computer Science, or a related field.

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.

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.