Data Engineer II, AWS Analytics Engineering

The AWS Analytics Engineering (AAE) organization is the analytics backbone of AWS — we build and operate the data platform that powers business decisions across more than 150 AWS services. Every insight surfaced to AWS product leadership, from service adoption trends to revenue drivers, flows through systems our team designs, builds, and maintains. We operate at massive scale — processing petabytes of data daily through thousands of jobs consisting of transformations, reporting queries, ingestions, and infrastructure management scripts.

Our engineers work directly with source systems to procure data, convert it into structured formats, build large-scale processing pipelines, design analytical data models, and maintain infrastructure with the highest security and compliance standards.

We are seeking a Data Engineer to join our team. This individual will be a significant and autonomous contributor, owning a major portion of the team's data architecture — solving difficult problems, building logical data models, and delivering data pipelines that are stable, performant, and consistently high quality. You will work with engineers and stakeholders across AWS to design data contracts, build ingestion flows, and deliver analytical models that increase self-service access to datasets and business effectiveness.

The ideal candidate applies appropriate technologies and best practices, writes pragmatic and maintainable code, and takes ownership of ongoing data quality. You are proficient with SQL, ETL, and data processing, with experience using cloud-based data services such as AWS EMR, Glue, Redshift, and Lake Formation. The candidate should have exposure to AI/ML technologies, including LLMs, and a foundational understanding of Agentic Frameworks — including autonomous agents, multi-agent orchestration, and tool integration.

You are trusted with autonomy in ambiguous environments where data design is not well defined, able to balance customer requirements with team priorities, and passionate about building data platforms using AI to accelerate the next generation of analytics at AWS scale.

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.

AWS values diverse experiences. Even if you do not meet all of the 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.

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.

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.

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.

• Identify and resolve data quality issues in processing tools, contribute to improvements and innovation, and ensure best practices in pipelines you design and maintain. For example:…