Are you passionate about building data products that power strategic insights? Do you enjoy thinking end-to-end—from raw data to analytics-ready pipelines? If you’re excited by the challenge of designing scalable data infrastructure that enables decision-making at scale, we’d love to talk to you.
We are a data and analytics engineering team embedded in the Finance organization, supporting AWS Infrastructure Services & Supply Chain Finance (AIS SCF). We own a broad portfolio of valuable datasets and are investing in modernizing our data infrastructure to enable deeper analytics, better self-service, and stronger business impact. Our vision is to build a high-quality data foundation that accelerates insight generation and enables long-term product innovation.
We are looking for an Analytics-focused Data Engineer who is as passionate about clean, scalable data systems as they are about understanding the business context behind the numbers. In this role, you’ll partner closely with data engineers, BIEs, and product managers, as well as finance and business stakeholders. You’ll work across data platforms, transformation frameworks, orchestration tools, data modeling, and visualization systems—to build solutions that deliver trusted data at scale.
The ideal candidate combines technical strength with business curiosity: someone who enjoys exploring systems and processes independently, understands how data reflects business performance, and wants to shape how data informs strategy. You should be comfortable working in ambiguity, learning new technologies, and communicating clearly with both technical and non-technical audiences. If you want to make an impact by building data products that inform decisions and drive innovation, this is the role for you.
Key job responsibilities
• Design, build, and maintain scalable, reliable, and reusable data pipelines and infrastructure that support analytics, reporting, and strategic decision-making.
• Develop data models and prepare datasets that are intuitive, well-documented, and aligned with both immediate business needs and long-term analytical goals.
• Partner with Business Intelligence Engineers, product managers, and finance stakeholders to translate ambiguous business questions into clear data solutions that inform strategy.
• Explore source systems, data flows, and business processes to uncover opportunities, ensure data accuracy and completeness, and drive improvements in data quality and usability.
• Take end-to-end responsibility for the datasets you own—ensuring they are well-documented, meet user needs, and continuously evolve as business requirements change.
• Enable self-service analytics by delivering high-quality, trusted datasets and promoting best practices in data access and usage.
• Continuously identify opportunities to improve data flow efficiency, reduce technical debt, and simplify data architecture.
• Stay current with evolving data technologies and evaluate new tools and frameworks to improve our data platform’s scalability and performance.
• Continuously look for ways to improve our data tools, practices, and pipelines to better support insight generation and strategic decision-making.
About the team
https://w.amazon.com/bin/view/IFBIT
