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

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 ...

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

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 ...

Corporate Tools

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 Startup information

See Spokane, WA salary details

$34.4K

$83.6K

$137.5K

How much do remote data analyst startup jobs pay per year?

As of Aug 30, 2026, the average yearly pay for remote data analyst startup 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.

What is a remote data analyst at a startup?

A Remote Data Analyst at a startup is a professional who collects, processes, and analyzes data to help the company make informed decisions, all while working from a remote location. Their work often involves creating reports, identifying trends, and providing actionable insights to support business growth and strategy. Since startups are fast-paced and dynamic, remote data analysts may also be expected to work with various teams, adapt to changing priorities, and use a wide range of analytical tools. Strong communication and self-motivation skills are essential for success in this role.

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

A Remote Data Analyst at a startup requires strong analytical skills, proficiency in statistics, and experience with data visualization, often supported by a degree in a quantitative field. Familiarity with tools like SQL, Python or R, and platforms such as Tableau or Power BI, as well as experience with cloud-based collaboration tools, is typically expected. Outstanding communication, self-motivation, and adaptability are soft skills that help individuals excel in a fast-paced, remote startup environment. These abilities are vital for delivering actionable insights, collaborating effectively with distributed teams, and driving rapid, data-informed decisions.

How do remote data analysts at startups typically collaborate with cross-functional teams despite working remotely?

Remote Data Analysts at startups often work closely with product managers, engineers, and marketing teams through frequent virtual meetings and collaborative tools like Slack, Zoom, and shared dashboards. Effective communication is key, as analysts need to clearly present their findings and translate data insights into actionable recommendations for different teams. The fast-paced startup environment means priorities can shift quickly, so flexibility and proactive engagement are important for staying aligned with the company's goals.

Is it possible to work remotely as a remote data analyst startup?

Remote data analyst roles are common in startups, allowing employees to work from anywhere with internet access. These positions often require skills in data analysis tools like Excel, SQL, or Python, and may involve flexible schedules. Employers typically prioritize strong analytical skills and self-motivation for remote work success.

What are popular job titles related to Remote Data Analyst Startup jobs in Spokane, WA?

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

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The top searched job categories for Remote Data Analyst Startup jobs in Spokane, WA are:

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Cities near Spokane, WA with the most Remote Data Analyst Startup job openings:

Remote Data Analyst Startup jobs near you
Infographic showing various Remote Data Analyst Startup job openings in Spokane, WA as of June 2026, with employment types broken down into 72% Full Time, 25% Part Time, and 3% Temporary. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $83,559 per year, or $40.2 per hour.

Data Engineer IV (Remote)

Spokane, WA • Remote

ROI Agency
See more jobs at ROI Agencyexternal

$117K - $140K/yr

Full-time

Re-posted 8 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