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Senior Cloud / Data Engineer (Data / Reconstruction / HIPAA)

Midjourney

San Francisco, CAFull-timePosted 3mo agoStill listed 4 days ago

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At a glance

Compensation
No compensation found
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

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Job overview

Midjourney is hiring a Senior Cloud / Data Engineer (Data / Reconstruction / HIPAA). Midjourney is seeking a Senior Cloud / Data Engineer to design and implement secure cloud pipelines for large scan datasets. This role involves building orchestration for GPU-accelerated reconstruction and analysis, defining end-to-end data lifecycle for medical imaging, and implementing security and compliance primitives for HIPAA/PHI. The ideal candidate will also build operational tooling for monitoring, alerting, and incident-driven improvements.

Key focus areas include Design and implement secure cloud pipelines that ingest very large scan datasets reliably and resumably., Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls., and Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility..

Successful candidates bring Strong Experience With Cloud Batch/Queueing/Orchestration, Experience Shipping Production Systems Handling Large Data Volumes, and Practical Security Mindset And Comfort Operating In Compliance‑Constrained Environments. Important skills include Cloud Pipeline Design, Cloud Pipeline Implementation, Orchestration, Data Lifecycle Definition, Security Primitive Implementation, and Compliance Primitive Implementation. Preferred (not required): Building Reliable Data Pipelines At Scale, Observability, Security By Default, and Privacy By Default.

Skills & qualifications

RequiredNice to have

Skills

Cloud Pipeline DesignCloud Pipeline ImplementationOrchestrationData Lifecycle DefinitionSecurity Primitive ImplementationCompliance Primitive ImplementationOperational Tooling BuildMonitoringAlertingRunbooksIncident-Driven ImprovementsCloud BatchMessage QueueStorage SystemsData Pipeline ReliabilityProduction SystemsPractical Security MindsetOperating in Compliance-Constrained EnvironmentsBuilding Reliable Data Pipelines at ScaleObservabilitySecurity by DefaultPrivacy by DefaultOwning Backend DetailsUnderstanding Compute TradeoffsSpecifying Cloud Resources

Qualifications

HIPAAPHIStrong Experience With Cloud Batch/Queueing/Orchestration, Storage Systems, and Data Pipeline ReliabilityExperience Shipping Production Systems That Handle Large Data Volumes and Failure-Prone Networks

Full job description

WHAT YOU’LL DO

  1. Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably.

  2. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls.

  3. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility.

  4. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews.

  5. 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.

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