Senior Cloud / Data Engineer (Data / Reconstruction / HIPAA)
Design and implement secure cloud pipelines for large medical imaging datasets and build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics and cost controls.
Skills required
About this role
What you’ll do
Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably.
Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls.
Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility.
Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews.
Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet.
What we’re looking for
Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability.
Experience shipping production systems that handle large data volumes and failure-prone networks.
Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments.
Useful experience
Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability.
Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails.
Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks.
Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.
