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Remote Healthcare Data Engineer Jobs in Spokane, WA

ROI Agency

Data Engineer IV (Remote)

Spokane, WA · Remote

$117K - $140K/yr

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 ...

Corporate Tools

Senior Data Engineer

Post Falls, ID · On-site +1

$150K/yr

This is a remote position, but if you're near one of our local offices, you're welcome to come ... As a Senior Data Engineer at Corporate Tools, you will work closely with our Software and Analyst ...

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All JobsHealthcare Data Engineer JobsRemote Healthcare Data Engineer JobsRemote Healthcare Data Engineer Jobs in Spokane, WA

Remote Healthcare Data Engineer information

See Spokane, WA salary details

$45K

$131.2K

$179.5K

How much do remote healthcare data engineer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for remote healthcare data engineer in Spokane, WA is $131,159.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,800.00 and $139,000.00 per year, depending on experience, location, and employer.

What does a remote healthcare data engineer do?

A Remote Healthcare Data Engineer designs, builds, and maintains data systems that collect, store, and process healthcare data, all while working from a remote location. They ensure that large volumes of medical records, patient information, and other healthcare-related data are organized and secure. Their work supports healthcare providers and researchers in making data-driven decisions, improving patient outcomes, and ensuring compliance with privacy regulations. Remote Healthcare Data Engineers often collaborate with data scientists, analysts, and IT teams to create efficient and scalable data pipelines tailored to the unique needs of healthcare organizations.

What skills and qualifications are needed to thrive as a remote healthcare data engineer?

To thrive as a Remote Healthcare Data Engineer, you need expertise in data architecture, database management, and healthcare data standards, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (e.g., AWS or Azure), and knowledge of healthcare-specific systems such as HL7 or FHIR is crucial. Strong problem-solving skills, attention to detail, and effective remote communication are standout soft skills in this role. These competencies ensure secure, accurate handling of sensitive health information and support effective data-driven decisions in healthcare organizations.

How does a remote healthcare data engineer collaborate with clinical and IT teams to ensure data accuracy and security?

Remote Healthcare Data Engineers frequently work cross-functionally with clinical staff, IT professionals, and data analysts to design, implement, and maintain secure data pipelines. They participate in virtual meetings to understand data requirements, clarify data definitions, and ensure compliance with healthcare regulations such as HIPAA. Collaboration tools and secure communication platforms are essential to share updates, resolve issues, and document workflows. This teamwork helps ensure that data is accurate, accessible, and protected, ultimately supporting improved patient outcomes and operational efficiency.

What is the difference between Remote Healthcare Data Engineer vs Remote Healthcare Data Analyst?

AspectRemote Healthcare Data EngineerRemote Healthcare Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; experience with data pipelinesBachelor's in Statistics, Data Analysis, or related; proficiency in data visualization
Work EnvironmentDevelops data infrastructure, manages pipelines, collaborates with engineersInterprets data, creates reports, supports decision-making
Industry UsageDesigns data systems for healthcare organizations, research institutionsAnalyzes healthcare data for insights, reporting, and compliance
Common Search/ComparisonOften compared for technical roles in healthcare data managementRelated but focuses on analysis rather than infrastructure

The main difference is that Remote Healthcare Data Engineers build and maintain data systems and pipelines, while Remote Healthcare Data Analysts interpret data and generate reports. Both roles require healthcare industry knowledge, but engineers focus on data infrastructure, whereas analysts focus on data insights.

What are popular job titles related to Remote Healthcare Data Engineer jobs in Spokane, WA?

For Remote Healthcare Data Engineer jobs in Spokane, WA, the most frequently searched job titles are:

What job categories do people searching Remote Healthcare Data Engineer jobs in Spokane, WA look for?

The top searched job categories for Remote Healthcare Data Engineer jobs in Spokane, WA are:

What cities near Spokane, WA are hiring for Remote Healthcare Data Engineer jobs?

Cities near Spokane, WA with the most Remote Healthcare Data Engineer job openings:

Remote Healthcare Data Engineer jobs near you
Infographic showing various Remote Healthcare Data Engineer job openings in Spokane, WA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $131,159 per year, or $63.1 per hour.

Data Engineer IV (Remote)

Spokane, WA • Remote

ROI Agency
See more jobs at ROI Agencyexternal

$117K - $140K/yr

Full-time

Re-posted 5 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