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Databricks Engineer Jobs in Seattle, WA (NOW HIRING)

Deloitte

Sr Databricks Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

As a Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will work with business ...

Databricks

Sr. Product Manager, Databricks Repos

Seattle, WA · Remote

$144K - $190K/yr

Founded by engineers - and customer obsessed - we leap at every opportunity to tackle technical ... Databricks Repos is the source control and workflow foundation that powers how data engineers, ML ...

Databricks

Senior Software Engineer - Backend

Bellevue, WA · On-site +1

$138K - $182K/yr

P-939 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are ... Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical ...

Databricks

Sr. Product Manager, Databricks AI

Seattle, WA · On-site

$148K - $204K/yr

RDQ127R47 At Databricks, we are passionate about enabling every organization to harness the power ... Partner with world-class engineering and research teams to transform cutting-edge AI advancements ...

Databricks

Sr. Product Manager, Databricks AI

Seattle, WA

$144K - $190K/yr

RDQ127R47 At Databricks, we are passionate about enabling every organization to harness the power ... Partner with world-class engineering and research teams to transform cutting-edge AI advancements ...

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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.

Databricks Engineer

PROLIM Global Corporation

Seattle, WA • On-site

Full-time

Re-posted 22 days ago

Job description

Job Titel: Databrick Engineer
Location: Seattle, WA
Duration: 6 months
Job ID: 10492558
Role Description
• Design and implement data pipelines in Azure Databricks for ingesting and transforming data from upstream systems, including SAP, PIPS, POS into WFM and UKG
• Optimize ETL/ELT workflows for performance and scalability
• Collaborate with Java/API developers to integrate event-driven triggers into data pipelines
• Implement data quality checks, schema validation, and error handling
• Support batch and near-real-time data flows for both operational and analytics use cases
• Work with Boomi and WFM teams to ensure data contracts and canonical models are enforced
Essential Skills
• Design and implement data pipelines in Azure Databricks for ingesting and transforming data from upstream systems, including SAP, PIPS, POS into WFM and UKG
• Optimize ETL/ELT workflows for performance and scalability
• Collaborate with Java/API developers to integrate event-driven triggers into data pipelines
• Implement data quality checks, schema validation, and error handling
• Support batch and near-real-time data flows for operational and analytics use cases
• Work with Boomi and WFM teams to ensure data contracts and canonical models are enforced
Desirable Skills
• Digital : Databricks
Experience Required
8-10

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