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Data engineer

Aberdeen
Response Informatics
Data engineer
Posted: 3 June
Offer description

Role summary:

The overall technical lead and architect. Designs the metadata schema, builds the simulation onboarding pipeline, deploys metadata embedding pipeline and OpenSearch k-NN vector store, and authors data export format spec for AI/ML use case. This role is the deepest technical seat on the engagement:

Key responsibilities

* 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


Nice-to-have / differentiators

* Prior simulation / CAE / HPC data lake experience (Ansys, Siemens NX, BETA CAE, OpenFOAM, etc.)
* Familiarity with surrogate model training data pipelines
* Experience with SageMaker Unified Studio or comparable governed data-mesh tooling (in case of required integration)
* Multi-cloud data engineering (AWS GCP) experience
* Published or contributed to AWS data architecture patterns or blueprints

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