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Databricks Engineer Jobs in Spokane, WA (NOW HIRING)

ROI Agency

Data Engineer IV (Remote)

Spokane, WA · Remote

$117K - $140K/yr

This is hands-on engineering position requiring the ability evaluate execution layer code. Data ... Expert-level proficiency with SQL, Spark, Python, Databricks, Delta Lake, Azure Data Factory, and ...

FocusKPI

Marketing Operations Analyst

Spokane, WA · On-site

Collaborate with cross-functional teams such as IT and engineering to integrate data from various ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

All JobsDatabricks Engineer JobsDatabricks Engineer Jobs in Spokane, WA

Databricks Engineer information

See Spokane, WA salary details

$60.2K

$112.9K

$205.3K

How much do databricks engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for databricks engineer in Spokane, WA is $112,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,400.00 and $134,000.00 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 Spokane, WA? For Databricks Engineer jobs in Spokane, WA, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Spokane, WA look for? The top searched job categories for Databricks Engineer jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Databricks Engineer jobs? Cities near Spokane, WA with the most Databricks Engineer job openings:
Databricks Engineer jobs near you
Infographic showing various Databricks Engineer job openings in Spokane, WA as of August 2026, with employment types broken down into 89% Full Time, 5% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $112,873 per year, or $54.3 per hour.

Data Engineer IV (Remote)

ROI Agency

Spokane, WA • Remote

$117K - $140K/yr

Full-time

Re-posted 21 days ago

Job description

*Due to NERC regulations US Citizenship, Green Card Hold, or Permanent Residency is required for this role.*

ROI Agency is partnered with an established client to fill a remote Data Engineer IV position on a team we have successfully supported for a few years.

This is hands-on engineering position requiring the ability evaluate execution layer code.


Data Engineer IV

Position Summary

The Principal Data Engineer / Architect (Data Engineer IV) is a senior technical leader responsible for defining the enterprise-wide data architecture, platform strategy, and governance standards. This role shapes how data is collected, modeled, processed, secured, and consumed across all applications and business domains, ensuring the long-term scalability, reliability, and performance of the organization’s data ecosystem.

Principal Data Engineers drive large-scale modernization, lakehouse and warehouse architecture, MDM adoption, metadata automation, Delta Lake strategy, multi-cloud integrations, and end-to-end data platform evolution. Operating with full autonomy, this role engages with Directors, senior architects, and cross-functional leaders to guide decisions that impact enterprise systems, analytics, compliance, and technology investments.

This position is both strategic and hands-on when needed—solving the hardest technical problems, creating reusable frameworks, and mentoring senior engineers to elevate overall data engineering maturity across the enterprise.

Essential Functions:

  • Own the long-term design and architecture of the enterprise data ecosystem, including ingestion, storage, modeling, lineage, governance, and analytics layers.
  • Design scalable lakehouse, Delta Lake, and distributed data architectures supporting advanced analytics, operational workflows, and integration across business domains.
  • Lead enterprise-wide modernization projects: warehouse migrations, domain modeling redesigns, governance uplift, streaming adoption, or cross-cloud data integrations.
  • Define and enforce standards for data modeling, lineage, metadata, MDM, quality, security, and compliance across all data teams.
  • Create reusable architectural patterns, frameworks, orchestrations, and platform components adopted across engineering groups.
  • Solve the most complex technical problems, including distributed system bottlenecks, data quality crises, lineage gaps, and multi-domain data reconciliation issues.
  • Guide cost optimization strategy for compute, storage, and orchestration workloads across the data platform.
  • Partner with enterprise architecture, analytics, InfoSec, product, and application engineering to ensure alignment with organizational strategy.·
  • Influence leadership decisions regarding data strategy, platform investments, tooling, and sprint/roadmap priorities.
  • Mentor senior engineers, conduct design reviews, and provide technical leadership across teams to raise the overall engineering bar.

Basic Qualifications:

  • Bachelor’s degree in CS/IT/Data Science or equivalent experience (Master’s preferred).
  • 10+ years experience in data engineering, data architecture, or distributed systems engineering.
  • Proven track record designing and implementing enterprise-scale data platforms with Lakehouse/Delta architectures.
  • Expert-level proficiency with SQL, Spark, Python, Databricks, Delta Lake, Azure Data Factory, and distributed processing.
  • Deep understanding of data modeling (conceptual, logical, physical), governance frameworks, MDM, metadata catalogs, and lineage systems.
  • Experience leading multi-team engineering initiatives and influencing architectural decisions at the leadership level.
  • Strong grounding in security, compliance, data privacy, and regulatory data handling.

Requirements:
None