Who This Is For
VP Bioinformatics
at genomics labs and precision medicine companies
Head of Data Science
at genomics labs and precision medicine companies
CTO/CIO
at genomics labs and precision medicine companies
Why This Matters
If flat-file VCF storage, ad hoc ETL scripts, or undocumented data lineage sound familiar, your platform is already limiting what your team can do.
- 5+ unchecked items in any single category are a signal that your data platform is actively limiting growth, compliance, or AI capability in that area
- Every item includes the "why it matters" and the specific tool or standard to use, from Apache Iceberg to ABAC access control to NIST GIAB benchmarking
- Category 2 (HIPAA & Compliance) and Category 4 (Bioinformatics Pipelines) carry explicit warnings: 2+ gaps here put you at high risk during an actual audit or clinical validation
What's Inside
Nine scored categories, 42 items total:
1. Data Architecture & Lakehouse
Iceberg/Delta Lake, medallion architecture, cloud-native platforms, lineage tracking, petabyte-scale design
2. HIPAA & Compliance
Architecture-level HIPAA controls, customer-managed KMS keys, ABAC, immutable audit trails under 45 CFR § 164.312(b), PHI masking, multi-framework compliance readiness
3. ETL & Data Pipelines
Orchestration, automated quality gates, FHIR R4 as first-class ingestion, pipeline alerting, HL7 v2 normalization
4. Bioinformatics & Genomic Pipelines
Workflow engines, clinical-grade variant callers, RNA-Seq/single-cell standards, VEP/gnomAD/ClinVar annotation, NIST GIAB benchmarking
5. Interoperability & FHIR
HL7-to-FHIR translation, US Core 6.1.0 conformance, ONC Inferno validation, standard EHR integrations, Bulk Data export
6. Real-Time Streaming
Kafka/Flink/Kinesis, TAT alerting, live dashboards, sample lifecycle tracking
7. Data Quality & Observability
Automated quality gates, drift monitoring, incident detection time, end-to-end lineage, terminology standardization
8. AI/ML Readiness
Production-ready data, feature stores, training warehouses, synthetic data for rare populations
9. Documentation & Governance
Architecture documentation, data dictionaries, version control
What You'll Walk Away With
A category-by-category score that shows exactly where your platform is strong and where it's exposed
The specific tool, standard, or regulation citation to close each gap, not a vague recommendation
A prioritized list of what to fix first if you're preparing for a HIPAA, CAP/CLIA, or SOC 2 audit
A clear, evidence-based case to bring to leadership if your AI initiatives are stalling on data readiness
Healthcare Data Engineering Checklist for Genomics Labs
42 items, nine scored categories, and a scoring guide. Delivered to your inbox as a PDF.