Develop and automate comprehensive tests for data pipelines, ETL/ELT processes, and cloud data platforms. Validate data quality, transformations, performance, scalability, and time-series biosensor outputs. Build synthetic datasets that replicate production data, identify anomalies and bottlenecks, and improve testing frameworks. Collaborate with data engineers and scientists to ensure reliable data throughout the lifecycle supporting regulated software-as-a-medical-device products.

Build and operate reliability systems for a cardiovascular data platform, including monitoring, SLIs, SLOs, incident response, automation, and observability. Investigate end-to-end failures across devices, connectivity, mobile applications, firmware, and cloud services. Analyze fleet-level reliability using Python, SQL, and BigQuery; automate manual checks; conduct postmortems; and improve telemetry to ensure complete, trustworthy clinical data delivery.

The Lead Software Quality Engineering, Backend will oversee validation of a cloud-based data platform, lead a team of engineers, and contribute to automation and verification strategies for healthcare technologies.