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Senior Databricks Data Engineer Jobs in Seattle, WA

Databricks

Sr. Product Manager, Databricks AI

Seattle, WA · On-site

$148K - $204K/yr

Partner with world-class engineering and research teams to transform cutting-edge AI advancements ... Engage directly with data and AI leaders to uncover new use cases - then design products that make ...

Databricks

Sr Software Engineer-Networking

Bellevue, WA · On-site

$157K - $213K/yr

(P-1286) At Databricks, we are passionate about enabling data teams to solve the world's toughest ... We are seeking experienced Senior Software Engineers with large-scale distributed system experience ...

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. Product Manager, Data Governance

Seattle, WA · On-site

$144K - $190K/yr

You will be a Sr Product Manager for Unity Catalog ( Unity Catalog is the metadata and governance ... that enable Databricks' data & AI product teams (ML/AI, Data Science & Engineering, Data ...

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All JobsDatabricks Data Engineer JobsSenior Databricks Data Engineer JobsSenior Databricks Data Engineer Jobs in Seattle, WA

Senior Databricks Data Engineer information

See Seattle, WA salary details

$67.7K

$144K

$208.8K

How much do senior databricks data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for senior databricks data engineer in Seattle, WA is $144,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,900.00 and $163,300.00 per year, depending on experience, location, and employer.

What is a Senior Databricks Data engineer?

Senior Databricks Data Engineers are experienced professionals who design, develop, and optimize large-scale data processing pipelines using the Databricks platform. They work with big data technologies like Apache Spark, Delta Lake, and cloud platforms such as Azure or AWS. Their responsibilities include building and maintaining ETL processes, ensuring data quality, and collaborating with data scientists and analysts to deliver reliable, high-performance data solutions. As senior engineers, they also mentor junior team members and contribute to architectural decisions.

How does a Senior Databricks Data engineer typically collaborate with data scientists and analysts on large-scale projects?

A Senior Databricks Data Engineer works closely with data scientists and analysts to design, build, and optimize data pipelines that enable advanced analytics and machine learning initiatives. They often participate in cross-functional meetings to understand data requirements, translate them into scalable ETL processes, and ensure data quality and accessibility. Regular collaboration also involves troubleshooting data issues, optimizing Spark jobs for performance, and sharing best practices for data management. This close teamwork ensures that analytical teams have reliable, timely, and well-structured data to drive insights and decision-making.

What are the key skills and qualifications needed to thrive as a Senior Databricks Data engineer, and why are they important?

To thrive as a Senior Databricks Data Engineer, you need advanced expertise in data engineering concepts, big data technologies, and proficiency in programming languages like Python or Scala, usually backed by a bachelor's degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (Azure, AWS, or GCP), and certifications like Databricks Certified Data Engineer are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams distinguish top performers in this role. These skills are essential to efficiently design scalable data solutions, optimize data workflows, and drive business insights in complex data environments.

What is the difference between Senior Databricks Data Engineer vs Data Engineer?

AspectSenior Databricks Data EngineerData Engineer
CredentialsTypically requires experience with Databricks, Spark, cloud platforms, and often certifications like Databricks Certified Data Engineer AssociateRequires knowledge of data pipelines, SQL, ETL tools, and often cloud platform experience, but less specialized in Databricks
Work EnvironmentWorks primarily within Databricks environment, focusing on big data processing and analyticsWorks across various data tools and platforms, including traditional ETL and cloud services
Industry UsageCommon in organizations leveraging Databricks for big data analytics and machine learningWidely used across industries for general data pipeline development and data management

The main difference is that a Senior Databricks Data Engineer specializes in using Databricks and Spark for big data solutions, often requiring specific certifications and experience. A Data Engineer has a broader focus on data pipeline development across various tools and platforms, with less emphasis on Databricks-specific skills.

Is a Senior Databricks Data Engineer in demand?

A Senior Databricks Data Engineer is in high demand due to the increasing adoption of cloud-based data platforms and the need for advanced data processing skills. Professionals with expertise in Spark, SQL, and cloud environments like Azure or AWS are particularly sought after in data-driven industries.

What are the most commonly searched types of Databricks Data Engineer jobs in Seattle, WA?

The most popular types of Databricks Data Engineer jobs in Seattle, WA are:

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

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

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

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

Senior Databricks Data Engineer jobs near you
Infographic showing various Senior Databricks Data Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $144,025 per year, or $69.2 per hour.

Senior Staff Software Engineer - App and Partner Ecosystem

Databricks

Seattle, WA • On-site

$139K - $183K/yr

Full-time

Re-posted 24 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.


Apply