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Databricks Engineer Jobs in Seattle, WA (NOW HIRING)

Databricks

Staff Software Engineer - Streaming

Seattle, WA · On-site

$182K - $247K/yr

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems ... The role We're seeking an experienced Staff Engineer to drive the technical direction of Spark ...

Databricks

Sr. Counsel, Product

Bellevue, WA · On-site

$219K - $302K/yr

GAQ427R191 Databricks is seeking a Senior Product Counsel to help the Databricks legal team provide cutting-edge, practical legal advice to Databricks' engineering and product management teams as we ...

Databricks

Principal Engineer, Authentication

Bellevue, WA · On-site

$266K - $365K/yr

P-1125 At Databricks, we are obsessed with enabling data teams to solve the world's toughest ... Our engineering teams build highly technical products that fulfill real, important needs in the ...

Databricks

Principal Engineer - Privacy

Seattle, WA · On-site

$220K - $297K/yr

P-1125 Summary At Databricks, we are obsessed with enabling data teams to solve the world ... Our engineering teams build highly technical products that fulfill real, important needs in the ...

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All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Seattle, WA

Databricks Engineer information

See Seattle, WA salary details

$67.7K

$127K

$231K

How much do databricks engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for databricks engineer in Seattle, WA is $127,038.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,600.00 and $150,800.00 per year, depending on experience, location, and employer.

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.

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 $90,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering can earn higher compensation, often including bonuses and benefits.

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 like AWS or Azure, making them valuable in data-driven organizations across various industries.

What are popular job titles related to Databricks Engineer jobs in Seattle, WA?

For Databricks Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Databricks Engineer jobs in Seattle, WA look for?

The top searched job categories for Databricks Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Databricks Engineer jobs?

Cities near Seattle, WA with the most Databricks Engineer job openings:

Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $127,038 per year, or $61.1 per hour.

Senior Staff Software Engineer - App and Partner Ecosystem

Databricks

Seattle, WA

$139K - $183K/yr

Full-time

Re-posted 20 days ago

Job description

RDQ126R35

About Databricks
At Databricks, we empower data teams to solve the world's toughest challenges-from security threat detection to cancer drug development. Our mission is to build the best data and AI infrastructure platform, enabling our customers to focus on innovation.

Our engineering teams push the boundaries of data and AI technology while ensuring our platform operates with the resilience, security, and scale that businesses need to succeed.

About the Role

We are developing a growing ecosystem of applications and partners on the Databricks Data Intelligence Platform. Our team creates frameworks, tools, and best practices to enable seamless integrations, helping developers and partners build impactful solutions.

As a Senior Staff Software Engineer, you will define the vision, architecture, and strategy for this ecosystem. You will play a key role in enabling customers to integrate cutting-edge applications, helping developers thrive on Databricks, and shaping the future of data and AI platforms.

Your Impact

  • Define and drive the ecosystem strategy for Databricks, a crucial pillar of our platform growth. Shape how applications and integrations enhance the Databricks experience for developers, partners, and customers.
  • Develop frameworks, APIs, and tools that make it seamless for partners and developers to build, integrate, and scale applications within the Databricks ecosystem.
  • Enable customers to integrate cutting-edge applications and specialized functionalities, helping them drive competitive differentiation and expand their AI and data capabilities.
  • Lead and mentor engineers across teams, providing technical guidance, architectural direction, and career development support. Foster a culture of innovation, best practices, and knowledge sharing.
  • Collaborate cross-functionally with product, engineering, and business development teams to align technical roadmaps with strategic business goals.
  • Engage with open-source communities and advocate for best practices in application development, data processing, and ecosystem enablement.
  • Represent Databricks at industry events and conferences, influencing the broader data and AI landscape while engaging with partners, customers, and developers to shape the future of our platform.

What We're Looking For

  • Deep passion for and knowledge of the broad data and AI industry. Experience contributing to open-source projects and engaging with developer communities is a plus.
  • 10+ years of experience building data-intensive applications or systems. Strong expertise in database systems (SQL, NoSQL, OLAP/OLTP) and big data processing (Apache Spark, Flink). Experience designing high-performance APIs (REST, GraphQL, gRPC) and managing integrations.
  • Strong understanding of data security, governance, and compliance frameworks (RBAC, GDPR, HIPAA), as well as cloud infrastructure (AWS, Azure, GCP), Kubernetes, Terraform, and CI/CD pipelines.
  • Strong leadership skills with experience driving cross-functional and cross-organizational (e.g. external partners) initiatives.
  • Ability to mentor engineers, influence architectural decisions, and advocate for best practices.
  • Excellent communication skills to evangelize Databricks' ecosystem vision internally and externally.
  • Bias for action and commitment to delivering high-quality solutions.

Join us in shaping the future of the Databricks ecosystem and enabling the next generation of data and AI innovation.


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