BI Analyst Jobs in Seattle, WA
BI Analyst jobs in Seattle are in strong demand, concentrated in South Lake Union, the Central Business District, and Bellevue across technology, healthcare, and e-commerce. Employers actively hiring include Amazon, Amazon Web Services, and Google. Scan the live roles below and apply to whichever ones fit.
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DESCRIPTION
The Central Infrastructure Analytics Team (CIAT) is the unified source for Infrastructure Operations data and business intelligence solutions across AWS's global data center fleet. We support Central Operations leaders running rack install, decommission, repair, logistics, capacity optimization, and network operations.
We are looking for a Business Intelligence Engineer to design and own customer-facing analytics products and to drive analytics adoption across our customer teams. You will partner with operations leaders to translate business questions into measurable KPIs, build dashboards and metric layers in QuickSight, and increasingly leverage GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — to multiply your impact across thousands of users.
Successful BIEs on this team are customer-obsessed, comfortable with operational ambiguity, and equally interested in building great dashboards and in teaching customers to build their own. They write strong SQL, communicate clearly with non-technical leaders, and treat GenAI as a tool they actively use rather than a topic to read about.
Key job responsibilities
- Design, build, and maintain dashboards and analytical reporting solutions in QuickSight that support InfraOps decision-making
- Partner with business and technical stakeholders to translate operational questions into KPIs, data products, and Weekly and Monthly Business Review (WBR/MBR) narratives
- Develop and present recommendations to senior leaders, including written narratives and verbal walk-throughs of insights
- Design Amazon Q topics and supporting datasets that enable customer analysts to self-serve on questions previously requiring a CIAT engagement
- Use CIAT's GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — as a primary part of the job
- Contribute to CIAT's analytics enablement programs that train Central Ops analysts on BI tools, query platforms, and GenAI capabilities
- Write SQL against the team's data warehouse and datalake to validate metrics, investigate data quality issues, and prototype analytics
A day in the life
Most days mix a few hours of focused build work — SQL development, dashboard iteration, metric validation — with stakeholder time. You might join a working session with a Logistics or Capacity Optimization team to walk through a metric definition, then sit with one of their analysts to review a query they wrote against CIAT's datalake. After lunch you might pair with a Data Engineer on the data model behind a new WBR metric, draft the narrative for that week's review, and review another BIE's pull request before logging off. On a different day, the focus is an Amazon Q topic for a domain that has been generating repeat ad-hoc requests — designing the supporting dataset, configuring synonyms, and testing answers against real questions customers have asked.
You will be in front of customers regularly — not constantly, but enough that you should enjoy that side of the work. The team partners closely with Data Engineers and Systems Development Engineers, so you will rarely be the only person on a problem.
About the team
CIAT gathers, transforms, and analyzes data for inventory, change-of-state, system health, safety, security, workload, and resource efficiency across AWS's global data center fleet. Our customers are the operations leaders who run rack install, decommission, repair, logistics, capacity optimization, and network operations. We are investing heavily in self-service and GenAI-powered analytics to expand the reach of the team beyond what any one BIE can deliver alone.
BASIC QUALIFICATIONS
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 1+ years of SQL, ETL or Oracle experience
- 1+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 1+ years of developing automated reporting experience
- 3+ years of in the job offered or a related occupation experience
- 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
PREFERRED QUALIFICATIONS
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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, Seattle - 99,500.00 - 160,000.00 USD annually
DESCRIPTION
The Central Infrastructure Analytics Team (CIAT) is the unified source for Infrastructure Operations data and business intelligence solutions across AWS's global data center fleet. We support Central Operations leaders running rack install, decommission, repair, logistics, capacity optimization, and network operations.
We are looking for a Business Intelligence Engineer to design and own customer-facing analytics products and to drive analytics adoption across our customer teams. You will partner with operations leaders to translate business questions into measurable KPIs, build dashboards and metric layers in QuickSight, and increasingly leverage GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — to multiply your impact across thousands of users.
Successful BIEs on this team are customer-obsessed, comfortable with operational ambiguity, and equally interested in building great dashboards and in teaching customers to build their own. They write strong SQL, communicate clearly with non-technical leaders, and treat GenAI as a tool they actively use rather than a topic to read about.
Key job responsibilities
- Design, build, and maintain dashboards and analytical reporting solutions in QuickSight that support InfraOps decision-making
- Partner with business and technical stakeholders to translate operational questions into KPIs, data products, and Weekly and Monthly Business Review (WBR/MBR) narratives
- Develop and present recommendations to senior leaders, including written narratives and verbal walk-throughs of insights
- Design Amazon Q topics and supporting datasets that enable customer analysts to self-serve on questions previously requiring a CIAT engagement
- Use CIAT's GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — as a primary part of the job
- Contribute to CIAT's analytics enablement programs that train Central Ops analysts on BI tools, query platforms, and GenAI capabilities
- Write SQL against the team's data warehouse and datalake to validate metrics, investigate data quality issues, and prototype analytics
A day in the life
Most days mix a few hours of focused build work — SQL development, dashboard iteration, metric validation — with stakeholder time. You might join a working session with a Logistics or Capacity Optimization team to walk through a metric definition, then sit with one of their analysts to review a query they wrote against CIAT's datalake. After lunch you might pair with a Data Engineer on the data model behind a new WBR metric, draft the narrative for that week's review, and review another BIE's pull request before logging off. On a different day, the focus is an Amazon Q topic for a domain that has been generating repeat ad-hoc requests — designing the supporting dataset, configuring synonyms, and testing answers against real questions customers have asked.
You will be in front of customers regularly — not constantly, but enough that you should enjoy that side of the work. The team partners closely with Data Engineers and Systems Development Engineers, so you will rarely be the only person on a problem.
About the team
CIAT gathers, transforms, and analyzes data for inventory, change-of-state, system health, safety, security, workload, and resource efficiency across AWS's global data center fleet. Our customers are the operations leaders who run rack install, decommission, repair, logistics, capacity optimization, and network operations. We are investing heavily in self-service and GenAI-powered analytics to expand the reach of the team beyond what any one BIE can deliver alone.
BASIC QUALIFICATIONS
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 1+ years of SQL, ETL or Oracle experience
- 1+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 1+ years of developing automated reporting experience
- 3+ years of in the job offered or a related occupation experience
- 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
PREFERRED QUALIFICATIONS
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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, Seattle - 99,500.00 - 160,000.00 USD annually
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Who's Hiring
- Amazon30
- Amazon Web Services13
- Google2
- TikTok2
- IntePros2
Top Industries Hiring
- Technology & Software
- Retail
- E-Commerce & Online Marketplaces
BI Analyst Jobs in Seattle: Frequently Asked Questions
How do I get a bi analyst job in Seattle?
The strongest path into Seattle's bi analyst market is through its dominant tech and cloud-services sector, where companies in South Lake Union and Bellevue hire continuously for roles tied to product analytics and operational reporting. Candidates who can demonstrate proficiency in Power BI or Tableau, combined with SQL fluency, stand out locally. Targeting healthcare systems and e-commerce companies in the greater metro also opens consistent opportunities at both mid-market and enterprise levels.
Which companies hire bi analysts in Seattle?
Employers hiring bi analysts in Seattle right now include Amazon, Amazon Web Services, and Google, based on current listings on Migrate Mate as of November 2026. Seattle's hiring landscape is especially active among large technology firms, regional healthcare networks, and retail and logistics companies headquartered in or near the metro.
Are there remote bi analyst jobs in Seattle?
Yes, bi analyst work is well-suited to remote arrangements given its desk-based, data-driven nature. About 55% of bi analyst openings tied to Seattle are remote or hybrid as of November 2026, reflecting how widely distributed analytics teams have become across the region. Dashboard development and reporting work in particular tends to be the most remote-friendly portion of the role among Seattle employers.
How can I get a bi analyst job in Seattle with little or no experience?
The most realistic entry point in Seattle is a junior or associate analyst role at a mid-size tech company or regional healthcare organization, where smaller teams often train candidates who show strong SQL fundamentals and data visualization skills. Internships at Seattle-area firms or lateral moves from roles in data entry, operations, or financial analysis provide a practical bridge. Building a portfolio of Power BI or Tableau dashboards using public datasets is a concrete way to demonstrate readiness to local hiring managers.
Which industries hire the most bi analysts in Seattle?
Most bi analyst openings in Seattle sit in Technology & Software, Retail, and E-Commerce & Online Marketplaces, per current listings on Migrate Mate as of November 2026. Seattle's outsized concentration of global technology headquarters, major hospital systems, and large-scale retail and logistics operations makes these sectors the dominant and most consistent sources of local bi analyst demand.
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