Principal Technology Strategist, Data Analytical Systems

Principal Technology Strategist, Data Analytical Systems Reports to: SVP, Laboratory Systems and Product Engineering Work Model: Remote (with periodic travel to San Carlos, CA and Austin, TX) Position Summary 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 RD 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." Key Responsibilities 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. Drive "Build-vs-Buy" decisions for pipeline workflow managers (e.g., WDL, Nextflow, Snakemake) and secondary analysis acceleration technologies (e.g., DRAGEN, GPU-based processing). Establish standards for data provenance and "Freeze-Down" protocols to ensure regulatory traceability across pipeline versions. Tertiary Analysis Clinical Interpretation Enable seamless integration between the "Dry Lab" results and “Wet Lab” QC metrics to deliver both operational and scientific insights to reviewers and lab directors. Lead the architectural design of Tertiary Analysis Platforms that integrate variant calling with large-scale knowledge bases for annotation and classification. Partner with RD and Clinical Ops to automate the Variant Classification workflow (ACMG/AMP guidelines), reducing manual curator burden through intelligent software design. Architect the Clinical Reporting Engine, ensuring it can handle complex multi-omic data, longitudinal results (MRD CGP), and dynamic template requirements for various global markets. Data Strategy Analytics Infrastructure Ensure data architectures comply with global privacy standards (HIPAA, GDPR) while maintaining the high availability required for clinical operations. Partner with the Lab Software Engineering leaders to ensure a seamless "hand-off" of data between the Wet Lab (LIMS) and the Dry Lab (Bioinformatics). Regulatory Excellence "Validation-at-Scale" Architect systems that support Continuous Validation, allowing for rapid pipeline updates without compromising clinical integrity or audit readiness. Lead the technical narrative for Data Analytical Systems during FDA (PMA/510k) submissions and CAP/CLIA inspections. Act as a mentor to the engineering and bioinformatics ... (truncated, view full listing at source)