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Amazon in Hyderabad is seeking a Data Engineer II to design and build scalable data pipelines that power analytics, ML, and BI across the organization. You will work with petabytes of data from thousands of sources, implementing real-time and batch ingestion using AWS tools and mentoring junior engineers.
This role emphasizes data modeling, warehousing, and building maintainable solutions that align with our broader data architecture across teams.
Join Amazon's Business Data Technologies team and help shape how millions of customers experience Amazon every day by designing and building the data infrastructure that powers our business. You'll work with petabytes of data from thousands of sources, creating scalable solutions that directly impact how we serve customers and make decisions across the organization.
As a Data Engineer II, you'll spend your time architecting and building large-scale data solutions that support analytics and insights across Amazon. You might start your day reviewing business requirements from stakeholders, then transition into designing data pipelines that ingest information from our catalog, inventory, and customer order systems in real time. You'll collaborate with peer engineers to evaluate different technical approaches, write and test code using tools like AWS Redshift, Spark, and Hive, and document your solutions so others can understand and build upon your work. Beyond your core responsibilities, you'll have opportunities to guide junior engineers through complex problems and contribute to discussions about which tools and technologies best serve our evolving needs.
We are the Business Data Technologies group within Amazon's eCommerce Foundation organization. Our mission is to collect, organize, and provide access to the massive amounts of data that drive Amazon's business—serving hundreds of thousands of data queries every single day. We work with internal customers across Amazon and our subsidiaries like IMDb and Audible to answer critical business questions and enable data-driven decision-making. We're building for scale, and we're looking for collaborative problem-solvers who are excited about working with complex datasets and translating business needs into technical solutions that our organization can rely on.
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