Key job responsibilities
Design, build, and own data pipelines that ingest, transform, and validate data center operational data from multiple source systems
Lead the migration of manual, high-maintenance data processes and legacy dashboards to automated, monitored pipelines
Design data models and publish trusted, reusable datasets that power automatically generated dashboards
Turn curated data into structured knowledge bases and Eva skills so insights show up directly in Eva
Set and enforce data quality, freshness, and monitoring standards, including alarms and runbooks
Find and retire brittle or duplicate data dependencies, and improve pipeline reliability and cost
Work with data center partners to understand their data sources and needs, then turn ambiguous asks into clear plans
Write clean, tested, documented code, take part in design and code reviews, and mentor junior engineers and interns
A day in the life
You might start the day reviewing pipeline health and deciding how to fix a recurring freshness issue at its source. Then you meet a data center operations partner to plan how a widely used dashboard's data moves into Eva. In the afternoon you write the design for a new ingestion pipeline, review a junior engineer's code, and work with the Eva platform team on how a new knowledge base plugs in. You finish by checking Eva's answers against your published data.
About the team
Eva Trust is part of the Data Center Gen AI team in AWS Infrastructure Services. We make sure Eva, the AI assistant used by 30K+ people across the data center community, is accurate, safe, and trusted, and that it brings up the right information where people need it. We own the data pipelines, dashboards, structured knowledge, evaluations, and guardrails behind Eva. We combine deep data center domain expertise with data and AI engineering, and we invest in growing the people around us.
Why AWS*
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences*
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance*
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture*
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth*
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
3+ years of data engineering experience
1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
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)
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
