Health & Life Sciences Platforms
HIPAA-aligned architectures spanning clinical workflows, RWD, and payer data with robust lineage and access controls.
- FHIR / HL7 integration
- PHI/PII safeguarding
- Data quality & observability
Focus
Health, Life Sciences & Multi-Omics Data Architecture
Building secure, interoperable data ecosystems that shorten the path from raw signals to actionable insight.
Multi-Omics & Research Data
End-to-end pipelines for genomics, proteomics, and imaging data with harmonized metadata models and reproducible processing.
- Variant pipelines & QC
- Metadata-driven orchestration
- Notebook-to-productization paths
Cloud-First Solution Architecture
Composable data mesh and lakehouse designs that enable domain teams without sacrificing governance.
- Snowflake / Databricks / BigQuery
- Lakehouse governance
- Cost-aware scaling & FinOps
Decision Intelligence
Analytics products that pair trusted data with clear narratives—dashboards, semantic layers, and AI-assisted insights.
- dbt & semantic modeling
- Executive-ready storytelling
- BI modernization
Blueprint
What a typical engagement looks like
- Assess & align. Map regulatory constraints, critical data domains, and decision pathways.
- Design. Blueprint target-state architecture, SLAs, and data contracts across domains.
- Build. Stand up ingestion, curation, and analytics layers with observability by default.
- Operationalize. Transition to product teams with runbooks, playbooks, and governance.
Highlights
Recent work
- Modernized a healthcare analytics stack with streaming FHIR ingestion, unified patient 360 modeling, and governed self-service BI.
- Built a multi-omics research platform combining sequencing data, clinical registries, and imaging assets with harmonized metadata and lineage.
- Delivered a Snowflake accelerator package for rapid data product onboarding with security controls, cost baselines, and observability patterns.
val product = pipeline()
.ingest("domain-context")
.validate(schema, contracts)
.curate(with="metadata")
.serve(via = ["warehouse", "api", "bi"])
Books & Learning
Writing & contributions
Talks