P-931
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. 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. As an engineering manager of an Infrastructure team, you will lead the creation and operation of scalable systems to build, validate, and deploy the Databricks Runtimes to a multi-cloud environment across the globe!
Key responsibilities include:
- Build and lead a talented engineering team that develops critical infrastructure needed to build and deploy our Databricks Runtime releases in a controlled and efficient manner
- Partner with our development teams to improve efficiency of release life cycle development activities
- Lead our release team by overseeing Databricks Runtime Releases to ensure high quality delivery of our standard, machine learning and Photon runtimes
- Oversee sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
- Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities
The impact you will have:
- Develop automated build, test, and release infrastructure to allow Databricks Runtime releases to be deployed to existing Cloud providers
- Support company-wide initiatives by adapting existing infrastructure for key company deliverables
- Enhance product release workflows for engineering and operational efficiency
- Use our own data and AI platform to analyze fleet metrics used for deployment safety and efficiency
- Set and uphold guidelines for release life-cycles, cadence and development workflows by owning a release pipeline capable of accommodating our engineering team and corporate release cadence objectives
- Manage technical debt, including long term technical architecture decisions and balance product roadmap
What we look for:
- BS (or higher) in Computer Science, or a related field
- 5+ years of experience building and leading a team of engineers working in a related system
- Passion for building highly scalable and reliable infrastructure
- Experience with cloud APIs and technologies e.g. a public cloud such as AWS, Azure, and/or GCP
- Experience with build, release and deployment infrastructure technologies such as Spinnaker, Jenkins, Airflow, Docker, Kubernetes, Terraform, Bazel, etc.
- Can ensure the team builds high quality and reliable infrastructure services; experience being responsible for testing, quality, and SLAs of a product; previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals
- Ability to attract, hire, and coach engineers who meet the Databricks hiring standards - can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of the team and guide their careers
- Comfort working on cross-functional projects with the ability to deeply understand product and customer personas
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.
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, please visit https://www.mybenefitsnow.com/databricks.
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.
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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.
