What roles does Databricks hire for?

Databricks commonly hires for software engineer, data engineer, machine learning engineer, solutions architect, product manager.

Databricks Resume Guide: Tips, Keywords & Examples (2026)

Does Databricks sponsor H-1B visas?

Yes. Databricks is an active H1B sponsor. It filed 172 certified H1B labor condition applications in FY2026 (Oct 2025 - Mar 2026), at a median certified wage of $173,732. The most sponsored role is Software Developers. Certified filings are the legal minimum wage the employer attests to pay, so actual total pay is often higher.

See Databricks’s full H1B salary and sponsorship data

What It's Like to Work There

Engineering-driven with a strong research mindset. Many employees have PhDs or deep academic backgrounds. Fast-paced and competitive. Open source ethos runs deep. Good compensation and equity.

Resume Tips for Databricks

Apache Spark experience is a major plus. Databricks created Spark and it's central to their platform.

Show experience with data lakehouse architecture, Delta Lake, or large-scale data processing. This is their core product area.

Highlight ML/AI experience, especially MLOps, model training at scale, or feature engineering. Databricks positions itself as an AI company.

Mention experience with Python, Scala, or Java. These are the primary languages in the Spark ecosystem.

Include any open source contributions, especially to Spark, Delta Lake, or MLflow. Databricks was built on open source and values contributors.

Show you can explain complex technical concepts simply. Databricks wants people who can work with both data engineers and business analysts.

Hiring Process

Recruiter screen, then a technical phone interview (coding or system design)

Onsite loop with 4-5 interviews covering coding, design, and behavioral

Some roles include a presentation or deep-dive on a past project

Process takes 2-4 weeks

Interview Style

Technical depth is expected. Coding interviews test fundamentals. System design rounds focus on distributed data systems. They'll ask about your understanding of data processing paradigms and may go deep on Spark internals for some roles.