Job Description & Details
This is a heavy-hitting senior role focused on modernizing legacy data infrastructure and building out agentic AI workflows on AWS. You aren't just writing basic ETL pipelines here; you are expected to architect end-to-end data systems and integrate cutting-edge generative AI tooling like Amazon Bedrock into production environments.
What You'll Actually Be Doing
You will spend your days migrating massive legacy on-premises data workloads into a clean, scalable AWS cloud ecosystem. Beyond standard data engineering duties like pipeline optimization and schema design, you are going to be building intelligent agents using Amazon Bedrock. Expect to collaborate heavily with data scientists and architects to turn complex unstructured data into functional GenAI applications that actually solve business problems.
The Core Tech Stack
You need to be an absolute expert in Python and core AWS data services including S3, Glue, Lambda, Redshift, EMR, and Step Functions. More importantly, real-world experience with Amazon Bedrock and Agentic AI workflows is what sets this role apart from a standard data engineering gig. The team relies on you to know how to ingest both structured and unstructured data seamlessly while keeping data governance and quality tight throughout the migration process.
Interview Expectations
Expect the hiring manager to grill you on your experience moving complex legacy databases to AWS with zero downtime, asking you to explain how you handled unexpected bottlenecks during the migration. You will also likely be asked to walk through the architecture of a production GenAI app you built using Amazon Bedrock, with the interviewer secretly probing to see if you actually understand the cost and latency trade-offs of foundation models versus just following tutorial code.
Application Advice
Do not just list every AWS certification you own; instead, highlight your specific war stories regarding on-premises cloud migrations and AI agent deployments right at the top of your resume. Make sure terms like "Amazon Bedrock," "Agentic AI," "ETL/ELT pipelines," and specific services like "Redshift" and "Glue" are prominently featured to easily clear the ATS filters and catch the hiring manager's eye.