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Description

AWS Data Center Capacity Delivery (DCCD) is looking for a Data Engineer to support data center construction globally. We work on the most challenging problems, with thousands of variables impacting the data center delivery — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, construction specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. You’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

We're looking for a Data Engineer to help us grow our Data Lake and Data Warehouse Systems, built on a serverless architecture with 100% native AWS components including
Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch, and more. We own a world-class data lake that drives multi-billion dollar decisions on a
regular cadence, and we're looking to improve on filling the lake quickly with as little human intervention as possible while democratizing the data within it.

In this role, you'll also help shape the next generation of our analytics platform by building agentic AI solutions and MCP (Model Context Protocol) servers that enable intelligent, autonomous data workflows. This includes designing AI-driven agents that can discover, query, and reason over our data lake — putting self-service analytics capabilities directly in the hands of stakeholders without requiring manual pipeline orchestration.

Our Data Engineers build ETL, analytics, and Gen AI-powered solutions for our internal customers to answer questions with data and drive critical improvements for the business. This includes building agentic AI workflows and MCP servers that put self-service analytics directly in stakeholders' hands. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. We are passionate about solving business problems with data!

Key job responsibilities

Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.

Design and build MCP servers and agentic AI workflows that enable autonomous data discovery, querying, and self-service analytics over our data lake.

Develop and integrate LLM-based solutions (e.g., Amazon Bedrock) to power natural language interfaces and intelligent automation across our analytics platform

Implement and support reporting and analytics infrastructure for internal business customers.

Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging.

Develop data objects for business analytics using data modeling techniques.

Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.

Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.

Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions.