Jobs at Databricks

Positions 10,585

Databricks, founded in 2013, built the Unified Data Analytics Platform that powers data lakes, machine learning, and analytics for Fortune 500 customers. The company is known for its open-source contributions to Apache Spark and for enabling real-time data pipelines.

Open roles span software engineering, data engineering, data science, product management, design, sales, and support. Candidates can expect rigorous technical interviews, collaborative cross-functional teams, and a culture that emphasizes learning and impact.

Job Transparency provides the exact salary ranges for each Databricks posting, along with recent employee reviews. This data lets you benchmark offers, negotiate confidently, and assess alignment with your career goals before applying.

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Frequently Asked Questions

What is it like to work at Databricks?

Databricks offers a collaborative environment where engineers and data scientists build end-to-end pipelines that serve millions of users. Employees enjoy flexible remote options, health benefits, competitive equity packages, and a focus on continuous learning through internal bootcamps, hackathons, and open-source contributions. The culture values transparency, rapid experimentation, and a mission to democratize data science.

What types of positions are available at Databricks?

The company hires across a broad spectrum: Software Engineers (backend, frontend, full-stack), Data Engineers, Machine Learning Engineers, Data Scientists, Product Managers, UX/UI Designers, Sales Engineers, Customer Success Managers, Technical Support, and marketing roles. Each team works on components of the unified analytics stack, from Spark optimization to cloud integration.

How can I stand out as an applicant for Databricks?

Show depth in Spark or distributed computing by contributing to open-source projects, publishing performance benchmarks, or creating personal notebooks that solve real problems. Highlight experience with cloud data services (AWS, Azure, GCP) and demonstrate a strong command of SQL, Python, or Scala. Prepare for interview by mastering algorithmic problems, system design scenarios, and practical use cases around data pipelines, and be ready to discuss how your work aligns with Databricks’ mission of simplifying data engineering.

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