Partner with ML engineers, data scientists, and eng teams to ship features.
Build and maintain data pipelines for feature-ready data.
Design and maintain scalable ML and AI workflows, including Bedrock/LLMs.
Automate ML lifecycle steps: data prep, training, inference, deployment, monitoring.
Collaborate across teams to deliver end-to-end apps and APIs/UX.
Leverage AI-assisted tools like GitHub Copilot and Claude to accelerate dev.

🎯 Requirements

5+ years as a Data Engineer, building and deploying AWS solutions.
Strong Python and JavaScript proficiency with production-grade code.
Hands-on AWS services: Lambda, S3, Glue, Athena, Kinesis, EC2/ECS, RDS.
Experience with NoSQL stores (MongoDB or similar).
Experience building and maintaining real-time, low-latency data streaming pipelines.
Solid SQL, data warehousing, ETL, and Data Lake concepts.

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