* Key responsibilities on this engagement
* • Run the Sprint 1 architecture review of the existing UAT codebase (S3 + Glue + S3 Tables + OpenSearch + Athena) and deliver written gap findings.
* • Design the metadata schema, taxonomy, and field catalogue (Light, Brain, Power).
* • Tune data orchestration — Glue jobs, Athena queries, S3 Tables config, scheduling. Lead the deep-dive technical sessions with analysts on visualization requirements
* • Build and validate the simulation data onboarding pipeline against real data — including the 30 GB-per-run acoustic spectra dataset.
* • Configure and validate the OpenSearch k-NN vector store and the Bedrock embedding pipeline.
* • Author the AI/ML data export format specification and the AI onboarding pattern document.
* • Co-design the API middleware blueprint with the Cloud Infrastructure Architect.
* Must-have
* Principal-level hands-on data engineering on AWS — 7+ years
* Deep production experience with S3, S3 Tables, Glue, Athena, and OpenSearch
* (including k-NN / vector search)
* Built and shipped vector embedding workloads
* Strong metadata modelling and data taxonomy design experience for scientific
* or engineering domains
* Comfort working with Parquet, JSON-LD, and large binary scientific data formats
* (mesh, time-series, spectra)
* Python proficiency; PySpark / Glue job tuning experience