Sr. Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Are you passionate about leveraging data to deliver actionable insights that impact the daily business decisions of AWS? Do you want to have an impact on making strategic deals come to life?

If so, we are looking for a Sr. Data Engineer to join the Strategic Customer Engagements team to develop a scalable data analytics platform. The Strategic Customer Engagements Deal Team works with our customers on commercial private pricing opportunities to meet their desired business outcomes while ensuring alignment with AWS business objectives.

In this role, you will be responsible for end-to-end development of data engineering solutions from the ground up. You should have expertise in the creation and management of datasets and the proven ability to translate data into meaningful insights through collaboration with Product Managers, Business Intelligence Engineers (BIEs), and business partners. You should be passionate about designing scalable analytics solutions for a fast-growing business.

This is a high-visibility role. The right candidate will possess excellent business and communication skills, be able to work with business owners to translate business problem statements into technical requirements. You should have a solid understanding of how to build efficient and scalable data infrastructure and data models. The role will leverage generative AI and AWS services to raise the bar on how the team consumes and acts on data and build the next generation of AI-enabled data platform.

Key job responsibilities

• Build and maintain backend data infrastructure for analytical platforms and applications, ensuring data is clean, fresh, and optimized for downstream consumption
• Lead architectural improvements that simplify complex data systems and transformations and proactively address deficiencies that create bottlenecks in the data infrastructure
• Translate business problem statements into technical data requirements, partnering with BIEs and product management and stakeholders to define what data products to build
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
• Leverage AWS services and GenAI to build next-generation data solutions that improve efficiency and unlock new analytical capabilities
• Build data pipelines purpose-built for LLM consumption and create data products and feature stores that serve GenAI applications in near real-time
• Lead design reviews for your team"s data architecture and actively participate in design reviews of related software and data systems