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Databricks Engineer Jobs in Pleasanton, CA (NOW HIRING)

Databricks

Sr Software Engineer- CXI

Mountain View, CA · On-site

$164K - $225K/yr

P-1640 At Databricks, we're passionate about enabling data teams to solve the world's toughest ... Founded by engineers and driven by customer obsession, Databricks takes pride in tackling hard ...

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All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Pleasanton, CA

Databricks Engineer information

See Pleasanton, CA salary details

$66.2K

$124.2K

$225.9K

How much do databricks engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for databricks engineer in Pleasanton, CA is $124,235.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,600.00 and $147,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

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 engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

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, and why are they important?

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.
What are popular job titles related to Databricks Engineer jobs in Pleasanton, CA? For Databricks Engineer jobs in Pleasanton, CA, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Pleasanton, CA look for? The top searched job categories for Databricks Engineer jobs in Pleasanton, CA are:
What cities near Pleasanton, CA are hiring for Databricks Engineer jobs? Cities near Pleasanton, CA with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Pleasanton, CA as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 8% Part Time, and 4% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $124,235 per year, or $59.7 per hour.

Staff Software Engineer, Observability

Databricks

Mountain View, CA • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
Databricks is a data and AI company dedicated to enabling data teams to solve complex problems through their advanced platform. The Staff Software Engineer in the Observability team will develop observability solutions to enhance the health and performance monitoring of the company's infrastructure and products. This role involves building observability platforms, managing cloud infrastructure, and mentoring engineers to improve technical excellence within the team.
Responsibilities:
• You will build the next generation of observability platforms that support billions of active time series and process petabytes of logs daily.
• You will manage infrastructure across nearly a hundred cloud regions, enabling all Databricks engineers and customers to monitor the reliability of our product.
• You will develop advanced workflows that accelerate incident diagnosis for Bricksters, allowing engineers to quickly derive insights from logs and metrics.
• You will leverage powerful capabilities of Databricks’ own data intelligence platform to push the boundaries of troubleshooting practices in the industry.
• You will uplevel monitoring and reliability practices across Databricks engineering, developing opinionated tools that set common standards for managing structured logs, metrics, alerts, dashboards, and oncall rotations.
• Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.
Qualifications:
Required:
• BS (or higher) in Computer Science, or a related field.
• 7+ years of production-level experience in one of: Go, Python, Java, Scala, Rust, C++, or similar languages.
• Experience in software development, in large-scale distributed systems.
• Experience driving large projects involving multiple teams.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Familiarity with observability infrastructure, monitoring patterns, and reliability practices.
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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