Engineering Manager - Platform Reliability
Skills & Technologies
Requirements
- Experience
- 5+ years
- Education
- Bachelor's degree
Joblaze summary
In the role of Engineering Manager for Platform Reliability at Databricks, the individual will oversee the development of scalable, reliable services and tools that enhance the operational capabilities of the engineering team across various cloud environments. Key skills include experience with large-scale distributed systems, engineering management, and the ability to navigate complex stakeholder priorities. This position is ideal for someone with over five years of engineering experience, including two years in a management role, who is adept at balancing immediate project needs with long-term infrastructure goals. Databricks emphasizes a culture of engineering excellence and collaboration
Joblaze insights
- Listed about a month ago on Joblaze — tracked directly from Databricks's career page.
- Databricks has 788 other open roles including Solutions Architect Greenfield (New Logo) Start Ups France, Sr. Solutions Engineer - AI Natives Business, Senior Solutions Architect.
- 399 active Cloud roles on Joblaze right now.
- 270 active Machine Learning roles on Joblaze right now.
- 230 active distributed systems roles on Joblaze right now.
Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this Engineering Manager - Platform Reliability role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Cloud, Machine Learning, Data Engineering, distributed systems.
- What seniority level is this role?
- Databricks targets lead candidates for this position.
- Is this full-time or contract?
- Full-time for this Engineering Manager - Platform Reliability role at Databricks.
From the original posting
P-1535
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 Lakebase Platform Reliability team's footprint spans multiple stacks, systems, and stakeholders. They include AI-powered tooling and workflows for customer management, real-time observability during incidents, monitoring and auditing systems that underpin compliance requirements, and customer-facing operational APIs and maintenance workflows. You'll contribute to the wider platform mission: building resource management infrastructure, reliable distributed services, and internal tools that help Databricks engineers operate confidently across clouds and environments.
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.
- Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way
- Lead development of 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.
What we look for:
- 5+ years of Engineering experience and 2+ years of Engineering Management experience.
- Experience with large-scale distributed services and the processes around testing, monitoring, and SLAs.
- Ability to align multiple stakeholders on competing priorities.
- Able to balance short-term delivery against long-term stability.
- 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. 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.