DE&A - AIML - Auto ML

Must-have	Nice-to-have / differentiators
Principal-level hands-on data engineering on AWS — 7+ years	Prior simulation / CAE / HPC data lake experience (Ansys, Siemens NX, BETA CAE, OpenFOAM, etc.)
Deep production experience with S3, S3 Tables, Glue, Athena, and OpenSearch (including k-NN / vector search)	Familiarity with surrogate model training data pipelines
Built and shipped vector embedding workloads	Experience with SageMaker Unified Studio or comparable governed data-mesh tooling (in case of required integration)
Strong metadata modelling and data taxonomy design experience for scientific or engineering domains	Multi-cloud data engineering (AWS GCP) experience
Comfort working with Parquet, JSON-LD, and large binary scientific data formats (mesh, time-series, spectra)	Published or contributed to AWS data architecture patterns or blueprints
Python proficiency; PySpark / Glue job tuning experience

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