AWS Global Network Delivery Services keeps the cloud running. We own the delivery and operation of all
AWS global infrastructure — every data center, every server, every cable that ensures hundreds of millions of customers have uninterrupted access to the services they depend on. We work on some of the hardest supply chain and infrastructure problems on the planet, with thousands of variables in play, and we're looking for exceptional people who want to help solve them.
You'll join a diverse,
cross-functional team of Product, TIPMS, network engineers, planners, builders and operations leaders globally and collaborate across
AWS to deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost. You will experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
We are seeking a Senior Business Intelligence Engineer who thrives with a startup mentality — someone who can move fast, think big, and partner directly with business and Senior leaders to turn ambiguous problems into clear, data-backed recommendations.
What makes this role exciting? You won't just build metrics and dashboards — you'll build context. You'll own building relevant and context driven source of truth datasets and metrics that track infrastructure delivery process from intake through deployment to decommission lifecycle, giving leaders end-to-end visibility into the health and efficiency of our delivery milestones. You'll partner closely with Data Engineering and Product and Software teams to design and build innovative self-service platforms that empower business teams to answer their own questions without waiting in a queue.
The ideal candidate is deeply analytical, endlessly curious, and energized by the challenge of mining complex datasets to surface insights that change how the organization operates. You ask sharp questions, dig relentlessly into the data, and aren't satisfied until you've identified not just what happened, but why — and what we should do about it. You understand that great BI isn't about just producing reports; it's about enabling decisions with the right timely tradeoffs. You'll build context-driven, well-documented datasets and innovative self-service tools that put data directly in the hands of the people who need it most, and you'll use the principles of data mining,
data modeling, and AI to evaluate business health and drive measurable improvement.
Key job responsibilities
* Partner cross-functionally to gather requirements and deliver end-to-end analytics solutions — translating ambiguous business questions into structured analytical approaches, data models, and scalable self-service tools
* Collaborate with Sr.Business Leaders, TiPM, Product, DE to transform large, complex datasets into structured, analytics-ready insights that drive business outcomes
* Design, develop, and deploy production-grade context driven datasets and pipelines for self serve, enforcing mandatory code reviews, data quality checks,
anomaly detection, and monitoring to ensure consistency, reliability, and reusability at scale
* Drive alignment on metrics definitions, taxonomy, and data governance across stakeholders
* Establish a BI platform enabling stakeholders to self-serve at scale
* Leverage AI to deliver practical and sophisticated solutions, pushing beyond conventional analytics approaches
* Mentor and develop junior team members — establishing and driving best analytics practices across the team
* Communicate results, insights, and recommendations across all levels of the organization — from engineering teams to senior leadership — distilling complex findings into clear, actionable narratives tailored to each audience
• Analyzing source data systems and driving best practices in source teams.
A day in the life
Mornings start with pipeline health checks and intake triage. Then you
go deep — scoping new metrics by understanding sources and questioning what business decisions they'll actually drive, before writing any code. Afternoons shift between refactoring legacy pipelines into modular, documented stages; presenting draft dashboards with honest caveats to leadership; and reviewing teammates' work. You close the day by documenting what you learned, pushing your CR, and making sure nothing stays only in your head. Every step is deliberate — understanding before building, transparency over polish.
About the team
We are the PAX Analytics team — a small, high-conviction group of BI Engineers and Data Engineers embedded in one of the world's largest and fastest-growing data center organizations. We were established less than a year ago with a clear mandate: **turn operational complexity into decision-ready clarity.**
We don't build dashboards. We build *context* — the kind that lets leaders act with confidence and operators spot problems before they become incidents. Our work spans the full data lifecycle: sourcing and integrating raw operational signals, engineering reliable pipelines at scale, and surfacing insights through self-service tools that hundreds of people rely on daily.
Every pipeline we ship, every standard we define, and every contract we establish becomes the foundation for what comes next
We are young, we are scrappy, and we are building something that will outlast us. If you want to lay foundations that an entire organization will stand on — you're in the right place.
- 7+ years of SQL,
ETL or
Oracle experience
- Experience in the data/BI space
- 6+ years of developing automated reporting experience
- Experience with
AWS technologies
- Experience in scripting for automation (e.g.
Python) and advanced SQL skills.
- Knowledge of data warehousing and
data modeling- Experience with data visualization using
Tableau, Quicksight, or similar tools
- Experience managing, analyzing and communicating results to senior leadership
- 6+ years of relevant professional experience in business intelligence, data engineering, or analytics engineering
- Experience working directly with business stakeholders to translate between data and business needs
- Master's degree in statistics, data science, or an equivalent quantitative field
- Experience using Cloud Storage and Computing technologies such as
AWS Redshift,
S3,
Hadoop, etc.
- Experience programming to extract, transform and clean large (multi-TB) data sets
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, VA, Herndon - 130,400.00 - 176,300.00 USD annually
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually