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Remote Data Analysis Jobs in Spokane, WA (NOW HIRING)

ROI Agency

Data Engineer IV (Remote)

Spokane, WA · Remote

$115K - $139K/yr

ROI Agency is partnered with an established client to fill a remote Data Engineer IV position on a ... Partner with enterprise architecture, analytics, InfoSec, product, and application engineering to ...

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 ... Partner with enterprise architecture, analytics, InfoSec, product, and application engineering to ...

micro1 AI

Cheminformatics Specialist - Remote

Spokane, WA · On-site +1

$90 - $120/hr

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

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 ...

DataAnnotation

FP&A Manager - AI Trainer

Spokane, WA · Remote

$50 - $100/hr

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

DataAnnotation

Treasury Analyst - AI Trainer

Spokane, WA · Remote

$50 - $100/hr

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

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Remote Data Analysis information

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, statistical knowledge, and a background in fields like mathematics, statistics, or computer science. Proficiency with data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management help remote analysts present insights clearly and stay productive without direct supervision. These skills and qualities ensure accurate data-driven decisions and effective remote collaboration with stakeholders.

What is the difference between Remote Data Analysis vs Remote Data Entry?

AspectRemote Data AnalysisRemote Data Entry
Required SkillsData interpretation, statistical tools, analytical skillsTyping speed, accuracy, basic computer skills
Tools UsedExcel, SQL, data visualization softwareSpreadsheets, data entry platforms
Work EnvironmentAnalytical tasks, report creation, data insightsData input, database updating, record management
Common CertificationsData analysis certifications, Excel proficiencyNone typically required

Remote Data Analysis involves interpreting data, creating reports, and providing insights using analytical tools, while Remote Data Entry focuses on inputting and managing data accurately. Both roles are performed remotely and require computer skills, but Data Analysis demands analytical expertise and familiarity with data tools, whereas Data Entry emphasizes speed and accuracy in data input tasks.

What is remote data analysis?

Remote data analysis refers to the process of examining, interpreting, and drawing insights from data using digital tools, while working from a location outside of a traditional office setting. Professionals in this field utilize statistical software, databases, and visualization tools to analyze large datasets and help organizations make informed decisions. Remote data analysts often collaborate with team members and stakeholders virtually, ensuring that data-driven strategies are implemented effectively. This role requires strong analytical skills, attention to detail, and the ability to communicate findings clearly.

How do remote data analysts typically collaborate with team members and stakeholders?

Remote data analysts often use a combination of communication and project management tools—such as Slack, Microsoft Teams, and Zoom—to stay connected with colleagues and stakeholders. Regular virtual meetings, shared dashboards, and collaborative platforms enable them to discuss findings, gather requirements, and provide updates on ongoing projects. Clear documentation and proactive communication are essential to ensure alignment, especially when working across different time zones or departments. Building strong relationships with team members virtually can help streamline workflows and facilitate effective decision-making.
What are the most commonly searched types of Data Analysis jobs in Spokane, WA? The most popular types of Data Analysis jobs in Spokane, WA are:
What are popular job titles related to Remote Data Analysis jobs in Spokane, WA? For Remote Data Analysis jobs in Spokane, WA, the most frequently searched job titles are:
What job categories do people searching Remote Data Analysis jobs in Spokane, WA look for? The top searched job categories for Remote Data Analysis jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Remote Data Analysis jobs? Cities near Spokane, WA with the most Remote Data Analysis job openings:
Remote Data Analysis jobs near you
Infographic showing various Remote Data Analysis job openings in Spokane, 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 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Engineer IV (Remote)

ROI Agency

Spokane, WA • Remote

$115K - $139K/yr

Full-time

Re-posted 19 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.

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