Reports to: SVP, Laboratory Systems and Product Engineering
Work Model: Remote (with periodic travel to San Carlos, CA and Austin, TX)
The Principal Technology Strategist for Data Analytical Systems is an enterprise technical leader responsible for the architectural vision of the "Dry Lab" informatics ecosystem. This role defines how we process, analyze, and interpret massive-scale genomic data—transforming raw sequencing output into life-saving clinical insights.
This strategist owns the long-term technical roadmap for Production Bioinformatics Pipelines and Tertiary Analysis Systems. You will architect the platforms that handle primary/secondary NGS analysis, variant annotation, clinical classification, and the complex orchestration of Clinical Report Writing. Your mission is to ensure our analytical systems are computationally efficient, scientifically rigorous, and compliant with global regulatory standards (FDA/CAP/CLIA).
In the first 90 days, you will conduct a deep-dive audit of our current bioinformatics infrastructure and reporting workflows. You will identify bottlenecks in processing latency and manual "scientist-in-the-loop" steps within the tertiary analysis phase. You will establish a working rapport with the Bioinformatics R&D and Clinical Operation teams to align on a unified "Production-Grade" vision.
Within the first year, you will have architected a scalable, cloud-native framework for "plug-and-play" bioinformatics pipelines that supports our entire portfolio (Oncology MRD/CGP, ECD, and Women’s Health). Success will be defined by a measurable reduction in computational cost-per-sample, increased automation in variant classification, and a modernized reporting workflow engine that significantly reduces the time from "Sequence-Complete" to "Report-Issued."
Production Bioinformatics & Pipeline Orchestration
Define the enterprise strategy for Production-Grade Bioinformatics, ensuring pipelines are robust, reproducible, and version-controlled for clinical use.
Architect high-performance computing and/or cloud-native orchestration layers that can scale elastically with laboratory volume.