We anticipate the application window for this opening will close on - 23 Jan 2026

 

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world.

A Day in the Life

Own the end-to-end serverless architecture for ingesting, validating, processing, and storing diabetes data (PHI) from connected devices, mobile apps, and clinical systems. Mentor engineers and elevate engineering practices across teams.

This position is an exciting opportunity to work with Medtronic's Diabetes business. Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements. This separation provides our team with a bold opportunity to unleash our potential, enabling us to operate with greater speed and agility. As a separate entity, we anticipate leveraging increased investments to drive meaningful innovation and enhance our impact on patient care.

Minimum Qualifications

• Requires a Baccalaureate degree and minimum of 10 years of relevant experience OR Master's degree with a minimum of 8 years relevant experience OR PhD with 6 years relevant experience.

Preferred Qualifications:

Design multi-channel ingestion using AWS serverless patterns:

• API Gateway + Lambda for app/API traffic
• Event-driven workflows with EventBridge, Step Functions, SQS/SNS for decoupling, retries, and DLQs
• Streaming pipelines via Kinesis Data Streams/Firehose; define schemas, versioning, and replay strategies
• Define processing pipelines in Lambda/Step Functions (and EMR/Spark if   needed for large transforms):
• Normalize, validate, deduplicate, and enrich time-series data (CGM/insulin events), handle clock skew, units, and data quality rules.
• Implement idempotent handlers, backpressure controls, and at- least/exactly-once semantics where appropriate
• Expose secure APIs via API Gateway with OAuth2/OIDC, fine-grained  scopes, consent-aware access, and full auditability
   

Architect storage and data models:

• DynamoDB for high-throughput operational workloads (session/state,  telemetry indexes, consent/access metadata); design keys, GSIs, TTLs, and global tables as needed.
• Amazon DocumentDB for semi-structured clinical/event documents; define collections, indexes, and consistency/read/write strategies.
• Amazon Redshift for analytics and longitudinal studies; model distribution/sort keys, data marts, and federated queries (Athena/Redshift Spectrum).
• Amazon S3 as the data lake (raw/curated zones) with lifecycle policies, compression/columnar formats (Parquet), and Glue Data Catalog for discovery

Implement security, privacy, and compliance by design:

• PHI safeguards: encryption at rest/in transit (KMS, TLS), least‑privilege   IAM, VPC isolation, PrivateLink/VPC endpoints, WAF/Shield as applicable.
• Secrets and key management (Secrets Manager/KMS), rotation policies, and tamper-evident audit trails (CloudTrail, Config).Ensure reliability, observability, and performance:
•  Define SLOs (ingestion latency, freshness) and build resilient, multi‑AZ  serverless designs with retries, DLQs, and circuit breakers
• Instrument metrics/logs/traces (CloudWatch, X‑Ray), alarms and runbooks; conduct load/performance and chaos/resilience testing.
• Optimize cold starts, concurrency, and throughput; apply caching and batching patterns when appropriate
   

FinOps leadership

• Own unit economics (per million messages, per API call, per active device), forecasts, and variance analysis
• Tagging/Cost Categories, CUR dashboards (Athena/QuickSight), Budgets/Anomaly Detection, showback/chargeback; service-level cost playbooks (DynamoDB capacity/table class, DocumentDB rightsizing
•  Lambda power tuning, log retention, NAT/data transfer reductions), and Savings Plans/RI strategy

Physical Job Requirements

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. 

The physical demands described within the Responsibilities section of this job description are re