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

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 ...

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 ...

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 ...

SEO Analyst

Post Falls, ID · On-site +1

$85K/yr

Overview As an SEO Analyst, your role is to make meaning out of messy data and help shape smarter ... This is a remote position. Our main office is in Spokane, WA, and we have satellite offices in ...

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Remote Data Analyst information

See Spokane, WA salary details

$34.4K

$83.6K

$137.5K

How much do remote data analyst jobs pay per year?

As of Jul 27, 2026, the average yearly pay for remote data analyst in Spokane, WA is $83,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,200.00 and $98,100.00 per year, depending on experience, location, and employer.

Is there a high demand for data analysts?

The demand for data analysts remains strong across various industries due to the increasing reliance on data-driven decision making. Organizations seek professionals skilled in data visualization, statistical analysis, and tools like Excel, SQL, and Python, leading to steady job growth in this field.

What are the key skills and qualifications needed to thrive as a Remote Data Analyst, and why are they important?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

Can I do a data analyst job remotely?

Yes, many data analyst positions are available for remote work, especially those that involve analyzing data, creating reports, and using tools like Excel, SQL, and data visualization software. Remote data analysts typically need strong communication skills and proficiency with relevant software to collaborate effectively with teams online.

Is 40 too late for data science?

For a remote data analyst role, age is generally not a barrier; many professionals transition into data science or analytics later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and tools like SQL or Python, regardless of age. Continuous learning and building a strong portfolio can help late entrants compete effectively in the field.

How do Remote Data Analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

What does a Remote Data Analyst do?

A Remote Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions, all while working from a location outside of a traditional office. They use statistical tools and software to interpret complex datasets, identify trends, and generate reports. Remote Data Analysts collaborate with team members via digital communication platforms and often present their findings to stakeholders to guide strategy and operations. Their work is essential in industries such as finance, healthcare, marketing, and technology, where data-driven decisions are crucial.

What is the difference between Remote Data Analyst vs Remote Data Scientist?

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

Will AI replace data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding context, and communicating findings, which currently require human judgment. Data analysts will likely evolve to work alongside AI, focusing more on complex analysis, strategy, and decision-making that AI cannot fully replicate.

What Does a Remote Data Analyst Do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

What are the most commonly searched types of Data Analyst jobs in Spokane, WA? The most popular types of Data Analyst jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Remote Data Analyst jobs? Cities near Spokane, WA with the most Remote Data Analyst job openings:
Infographic showing various Remote Data Analyst job openings in Spokane, WA as of July 2026, with employment types broken down into 82% Full Time, 9% Part Time, and 9% Contract. Highlights an 100% Remote job distribution, with an average salary of $83,559 per year, or $40.2 per hour.

Data Engineer IV (Remote)

ROI Agency

Spokane, WA • Remote

$117K - $140K/yr

Full-time

Posted 4 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