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Databricks Engineer Jobs in California (NOW HIRING)

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Databricks Engineer information

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$58.7K

$110.2K

$200.3K

How much do databricks engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for databricks engineer in California is $110,170.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,400.00 and $130,800.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Databricks engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data architecture can earn higher compensation, often exceeding $160,000 per year.

What is a Databricks engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

What are the key skills and qualifications needed to thrive as a Databricks engineer?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.

Is a Databricks engineer in demand?

Databricks engineers are in high demand due to the growing adoption of cloud-based data analytics and machine learning platforms. They typically require skills in Spark, SQL, and cloud environments, and their roles are often available across various industries seeking data-driven solutions.
What are popular job titles related to Databricks Engineer jobs in California? For Databricks Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in California look for? The top searched job categories for Databricks Engineer jobs in California are:
What cities in California are hiring for Databricks Engineer jobs? Cities in California with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in California as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $110,170 per year, or $53 per hour.

Sr. Product Manager, Databricks Repos

Databricks

San Francisco, CA • On-site

$149K - $196K/yr

Full-time

Re-posted 4 days ago

Job description

Job Summary:
Databricks is a data and AI company passionate about enabling data teams to solve complex problems. The Sr. Product Manager for Databricks Repos will drive the vision and roadmap for the platform, focusing on improving the developer experience and integrating with various Git providers.
Responsibilities:
• You will design the end to end path to production experience for data and AI teams, from authoring to Git integration to CI and CD.
• You will define how Repos integrates with GitHub, GitLab, and Azure DevOps to support branching, pull requests, reviews, conflict resolution, and deployment workflows.
• You will partner with engineers to build AI assisted code management features such as automated code suggestions, recommended diffs, merge help, and deployment validation.
• You will represent the voice of the customer and translate user feedback into workflow improvements that simplify source control and release management.
• You will improve developer productivity and reliability by aligning Repos with Databricks Workflows, Lakeflow, and deployment surfaces.
• You will help grow adoption of Databricks developer tools by working closely with solutions architects, customer success teams, and enterprise platform owners.
• You will grow end-user engagement with Databricks developer tools working closely with sales and customer success teams.
Qualifications:
Required:
• 5+ years of experience as a Product Manager working on platform products
• Experience building developer-facing products (tools, frameworks, SDKs) with tens or hundreds of thousands of users
• Experience being a hands-on builder, must be comfortable using our own developer-facing products.
• Passion for designing products that simplify user experience of technically complex products.
Company:
Databricks is a data and AI platform that unifies data engineering, analytics, and machine learning on a lakehouse architecture. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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