Role at a glance
- Salary
- $217K – $312.2K/yr
- Location
- San Francisco, California, United States Mountain View, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
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Role Summary
The Senior Engineering Manager will lead the Workspace Platform team in developing unified infrastructure for customer-facing Databricks capabilities, including content discovery and organization, collaborative code editing, and repository management. The role guides approximately 20 software engineers and drives shared platform capabilities that support Databricks Workspace products and integrations.
What You'll Do
- Define and drive the technical strategy for the Workspace Platform.
- Own the platform roadmap, execution, and delivery.
- Establish team practices for design reviews, code quality, testing strategies, and performance optimization.
- Partner with product and infrastructure teams across the organization to support seamless integration and innovation.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
15+ years of software engineering experience; 5+ years of engineering management experience, including managing other managers; experience scaling engineering teams from 10 to 30+ engineers; experience leading platform teams and backend developers in a SaaS environment; experience designing and building scalable distributed systems; familiarity with containerization technologies; expertise in distributed systems, AWS, Azure, GCP, and modern web application architectures; ability to collaborate across product, engineering, and business teams.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
RDQ225R488
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.
The Workspace Platform team is on an ambitious mission to scale our customer base 100x and support the future of agentic AI workloads. Our goal is to build a unified, consistent, and foundational Shared Platform for the entire Databricks Workspace experience.
As a Senior Engineering Manager on the Workspace Platform team, you will lead the development of unified infrastructure powering critical customer-facing capabilities across multiple Databricks products, including Content Discovery (akin to Google Search), Content Organization (akin to Google Drive), Collaborative code editing, and Repository management (akin to Github). This is a high-impact, exciting opportunity to guide a team of ~20 software engineers in creating platform features, intuitive workspace experiences, and partner integrations that are essential to Databricks' expansion and user adoption.
The impact you will have:
- Strategy & Vision: Define and drive the technical strategy for the Workspace Platform, including building over 16 shared capabilities that underpin the entire Databricks experience.
- Execution Ownership: Own the roadmap, execution, and delivery for the platform, ensuring all team deliverables meet the highest standards of quality and timeliness.
- Engineering Excellence: Establish and enforce team best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations for high-volume distributed systems.
- Cross-Functional Collaboration: Partner closely with teams across the organization, including those developing vertical product experiences (Lakehouse Platform, SQL Warehouse, AI/BI Dashboards, UC Platform) and core infrastructure, to ensure seamless integration and innovation.
What we look for:
- Experience: 15+ years of software engineering experience with a strong track record of technical leadership and impact.
- Management: 5+ years of engineering management experience, including experience managing other managers.
- Scaling: Proven experience scaling engineering teams from 10 to 30+ engineers.
- Platform Expertise: Experience leading platform teams and backend developers in a SaaS environment.
- Technical Depth:
- Experience designing and building scalable distributed systems.
- Familiarity with building services on top of containerization technologies.
- Expertise in distributed systems, major cloud platforms (AWS, Azure, GCP), and modern web application architectures.
- Collaboration: Strong ability to collaborate across product, engineering, and business teams to align technical strategy with core company growth objectives.
- Passion: A passion for building and scaling robust, high-performance platforms.
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 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.