Data Operations Analyst Jobs in Washington
Data Operations Analyst jobs in Washington are in strong and consistent demand, concentrated in technology, cloud services, healthcare, and aerospace sectors, with openings at every level from entry-level through senior and lead roles. Seattle, Bellevue, and Redmond account for most of the hiring activity, anchored by major employers like Amazon, Microsoft, and Boeing, all of which maintain large data and analytics operations in the state. The most in-demand specialties include data pipeline management, business intelligence, and ETL process development. Find a role that fits below and apply directly.
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DESCRIPTION
As a Data Engineer on this team, you will build and scale the data infrastructure behind this source-of-truth dataset, enabling finance and operations teams to assess network execution and understand cost drivers. This role sits at the center of network topology analytics, where the ability to understand Amazon's complex supply chain network and drive data model, mapping, and dimensional standardization is critical. You will onboard 100+ metrics into our central "metrics-as-a-code" platform enabling self-service reporting and analytics for finance and controllership teams. You will design, implement, and support scalable data solutions and complex data models for Amazon's Operations Finance organization. Your work will integrate heterogeneous data sources, automate ETL workflows, and deliver curated datasets used for reporting, analysis, and ad-hoc requests. You will partner with finance stakeholders, BI Engineers, and product teams to gather requirements, architect pipelines, and ensure that data is reliable, accessible, and trusted for data-driven business decisions.
Key job responsibilities
- Design, build, and maintain scalable ETL pipelines and data solutions using Python, SQL, Spark, and AWS services (S3, Glue, Redshift, Airflow, EMR, Lambda)
- Create coherent logical and physical data models that drive the metadata-driven configuration layer, enabling finance teams to define new metrics and views without code changes
- Collaborate with finance stakeholders, BI Engineers, and partner teams to gather requirements, integrate automated and manual data feeds, and deliver trusted datasets
- Participate in code reviews, design discussions, and team planning while identifying process improvements that increase automation and reduce manual error
- Optimize query performance and resource usage across the data platform, ensuring reliability and operational excellence at scale
A day in the life
You start your morning reviewing pipeline health dashboards and triaging data quality alerts on cost data flowing across transportation segments. Mid-morning, you collaborate with finance analysts to validate cost allocation logic for a carrier segment being onboarded into the platform. After lunch you build and test an ETL module that integrates a partner team's operational data feed, then pair with a teammate on a code review to ensure the solution scales across regions. Your afternoon wraps up with a design session on extending item-level cost granularity to support new reporting dimensions.
About the team
Our team within Operations Finance builds and operates the self-serve data platform that powers financial reporting, bridging, and analytics for over 2,500 finance customers across multiple regions. We support 10+ data producer teams and are focused on scaling automation, improving data quality, and incorporating AI-driven workflows for both our builders and customers. If you want to shape how a global finance organization interacts with data, this is the place to do it.
BASIC QUALIFICATIONS
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Knowledge of distributed systems as it pertains to data storage and computing
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience building large-scale, high-throughput, 24x7 data systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 132,100.00 - 178,800.00 USD annually
DESCRIPTION
As a Data Engineer on this team, you will build and scale the data infrastructure behind this source-of-truth dataset, enabling finance and operations teams to assess network execution and understand cost drivers. This role sits at the center of network topology analytics, where the ability to understand Amazon's complex supply chain network and drive data model, mapping, and dimensional standardization is critical. You will onboard 100+ metrics into our central "metrics-as-a-code" platform enabling self-service reporting and analytics for finance and controllership teams. You will design, implement, and support scalable data solutions and complex data models for Amazon's Operations Finance organization. Your work will integrate heterogeneous data sources, automate ETL workflows, and deliver curated datasets used for reporting, analysis, and ad-hoc requests. You will partner with finance stakeholders, BI Engineers, and product teams to gather requirements, architect pipelines, and ensure that data is reliable, accessible, and trusted for data-driven business decisions.
Key job responsibilities
- Design, build, and maintain scalable ETL pipelines and data solutions using Python, SQL, Spark, and AWS services (S3, Glue, Redshift, Airflow, EMR, Lambda)
- Create coherent logical and physical data models that drive the metadata-driven configuration layer, enabling finance teams to define new metrics and views without code changes
- Collaborate with finance stakeholders, BI Engineers, and partner teams to gather requirements, integrate automated and manual data feeds, and deliver trusted datasets
- Participate in code reviews, design discussions, and team planning while identifying process improvements that increase automation and reduce manual error
- Optimize query performance and resource usage across the data platform, ensuring reliability and operational excellence at scale
A day in the life
You start your morning reviewing pipeline health dashboards and triaging data quality alerts on cost data flowing across transportation segments. Mid-morning, you collaborate with finance analysts to validate cost allocation logic for a carrier segment being onboarded into the platform. After lunch you build and test an ETL module that integrates a partner team's operational data feed, then pair with a teammate on a code review to ensure the solution scales across regions. Your afternoon wraps up with a design session on extending item-level cost granularity to support new reporting dimensions.
About the team
Our team within Operations Finance builds and operates the self-serve data platform that powers financial reporting, bridging, and analytics for over 2,500 finance customers across multiple regions. We support 10+ data producer teams and are focused on scaling automation, improving data quality, and incorporating AI-driven workflows for both our builders and customers. If you want to shape how a global finance organization interacts with data, this is the place to do it.
BASIC QUALIFICATIONS
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Knowledge of distributed systems as it pertains to data storage and computing
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience building large-scale, high-throughput, 24x7 data systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 132,100.00 - 178,800.00 USD annually
See All 8 Data Operations Analyst Jobs in Washington
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Find Data Operations Analyst JobsData Operations Analyst Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Data Operations Analyst Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
What Washington Employers Look For
The qualifications that appear most often in data operations analyst jobs across Washington.
- Bachelor's degree in data science, computer science, information systems, or a related field
- Proficiency in SQL for querying, transforming, and maintaining large operational datasets
- Experience with ETL tools, data pipeline platforms, or workflow automation systems
- Familiarity with cloud data environments such as AWS, Azure, or Google Cloud Platform
- Ability to build dashboards and reports using business intelligence tools like Tableau or Power BI
- Strong attention to data quality, documentation practices, and cross-team communication skills
Data Operations Analyst Jobs in Washington: Frequently Asked Questions
How do you become a data operations analyst in Washington?
A bachelor's degree in data science, information systems, computer science, or a related field is the standard entry point for data operations analyst roles in Washington. No state-issued license is required for this role. Washington employers, particularly in the Seattle and Bellevue tech corridor, consistently prioritize candidates who demonstrate proficiency in SQL, cloud data platforms, and ETL processes, whether through coursework, certifications from providers like Google or Microsoft, or hands-on project work.
Which companies hire data operations analysts in Washington?
Employers hiring data operations analysts in Washington right now include Amazon and Meta, based on current listings on Migrate Mate as of September 2026. Washington's dense concentration of technology, healthcare, and aerospace companies means demand for this role is distributed across both large enterprise employers and mid-size firms throughout the greater Seattle metropolitan area.
Which Washington cities have the most data operations analyst jobs?
Seattle and Bellevue have the most data operations analyst openings in Washington. Seattle and Bellevue drive the bulk of the volume through their concentration of large technology firms and corporate headquarters, while Redmond specifically benefits from Microsoft's extensive data and analytics operations anchored there.
How can I get hired as a data operations analyst in Washington with little or no experience?
The most realistic path is applying to data analyst associate or junior data operations roles at Washington's large technology employers, which regularly hire recent graduates. Amazon and Microsoft both run new-grad and early-career programs in the Seattle area that place candidates into data operations tracks. Transitioning from adjacent roles such as business analyst, data quality specialist, or reporting analyst is also a well-established route. Completing a recognized data certification, such as the Google Data Analytics Certificate or a Microsoft Azure data credential, and building a portfolio of SQL and pipeline projects can give candidates a clear edge in a competitive field.
Where can I find and apply to data operations analyst jobs in Washington?
You can find and apply to data operations analyst jobs in Washington on Migrate Mate, which lists current Washington openings. Find roles that fit your experience and location, then apply directly to each one.
See All 8 Data Operations Analyst Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
Find Data Operations Analyst Jobs