Engineering Manager - Backend

Reposted Yesterday
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Amsterdam, NLD
In-Office
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Lead and grow a backend engineering team building scalable, cloud-agnostic infrastructure and services for Databricks. Hire and develop engineers, ensure engineering excellence (architecture reviews, testing, monitoring), drive roadmaps with product leadership, and coordinate cross-team execution to deliver reliable distributed systems and ML infrastructure.
Summary Generated by Built In

P-138

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.

As an Engineering Manager, you will work with your team to build infrastructure and products for the Databricks platform at scale. We have multiple teams working on different domains.

  • Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way
  • Develop reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers
  • Build tools to allow Databricks engineers to operate their services across different clouds and environments
  • Build services, products and infrastructure at the intersection of machine learning and distributed systems.

The impact you will have:

  • 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:

  • Experience with large-scale distributed web services and the processes around testing, monitoring, and SLAs.
  • Partner with PM, Sales, and Customers to develop innovative features.
  • BS (or higher) in Computer Science, or a related field.
  • 5 years of Engineering experience and 2 years of Engineering Management experience.

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, LinkedIn 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 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.

Skills Required

  • BS (or higher) in Computer Science or related field
  • 5 years of engineering experience
  • 2 years of engineering management experience
  • Experience with large-scale distributed web services, including testing, monitoring, and SLAs
  • Experience building cloud-agnostic services across cloud providers
  • Experience working with product, sales, and customers to develop features
  • Experience at the intersection of machine learning and distributed systems

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Equity Value & Accessibility Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
  • Healthcare Strength Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
  • Parental & Family Support Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.

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The Company
New York, NY
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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