Business Intelligence Intern Jobs in Seattle, WA
Business Intelligence Intern jobs in Seattle are concentrated in South Lake Union, the Denny Triangle, and the Eastside corridor, across cloud technology, e-commerce, and health tech. Employers actively hiring include Amazon, Amazon Web Services, and Google. Find a role that fits below and apply directly.
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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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Find JobsBusiness Intelligence Intern Job Market in Seattle
Who's Hiring
- Amazon28
- Amazon Web Services11
- Google2
- TikTok2
- IntePros2
Top Industries Hiring
- Technology & Software
- Retail
- E-Commerce & Online Marketplaces
Business Intelligence Intern Jobs in Seattle: Frequently Asked Questions
How do I get a business intelligence intern job in Seattle?
Start by targeting Seattle's dominant sectors: cloud and enterprise software companies in South Lake Union and the Eastside, e-commerce operations downtown, and health tech firms scattered through the broader metro. Employers here look for candidates who can work with large datasets, translate findings into dashboards, and communicate clearly with non-technical stakeholders. Familiarity with tools like SQL, Tableau, or Power BI gives you a concrete edge in this market.
Which companies hire business intelligence interns in Seattle?
Seattle business intelligence intern roles are posted by Amazon, Amazon Web Services, and Google and others right now, based on current listings on Migrate Mate as of November 2026. The local market includes a strong mix of global tech companies, regional healthcare systems, and fast-growing e-commerce and logistics firms, many of which run structured intern programs tied to their analytics or data engineering teams.
Are there remote business intelligence intern jobs in Seattle?
Yes, and business intelligence intern work is well-suited to remote arrangements given its analytical and desk-based nature. About 60% of business intelligence intern openings tied to Seattle are remote or hybrid as of November 2026, reflecting how broadly Seattle tech and data teams have adopted flexible work. Dashboard development, data cleaning, and reporting tasks are most commonly done off-site, while team onboarding and stakeholder presentations often require in-person attendance.
How can I get a business intelligence intern job in Seattle with little or no experience?
The most realistic entry path in Seattle is through university recruiting programs at large tech and e-commerce companies, which regularly hire interns with no prior industry experience if candidates can demonstrate SQL and data visualization skills. Building a small portfolio of self-directed projects using public datasets and posting them to GitHub signals readiness to Seattle employers who screen applicants quickly. Smaller health tech and retail analytics teams in the metro also hire entry-level interns who show initiative and basic tool proficiency.
Which industries hire the most business intelligence interns in Seattle?
Seattle business intelligence intern roles concentrate in Technology & Software, Retail, and E-Commerce & Online Marketplaces, based on current listings on Migrate Mate as of November 2026. Seattle's outsized presence in cloud infrastructure, global e-commerce, and integrated health systems creates persistent demand for interns who can support data pipelines, reporting workflows, and business performance analysis across all three sectors.
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