Healthcare & Life SciencesNorth America | Healthcare & Life Sciences | Three Successive Engagements

Enterprise Databricks Lakehouse & ETL Modernization

The Enterprise Challenge

Global healthcare and life-sciences organizations require scalable data pipelines to unify clinical research, supply chain logistics, and commercial operations while retiring high-cost, fragile legacy ETL infrastructure.

What We Delivered:

OrchV engineered an enterprise-grade cloud data architecture across three successive delivery phases: (1) Databricks Lakehouse & Delta Lake Deployment: Implemented a high-throughput Databricks Lakehouse on Microsoft Azure using PySpark to ingest and transform clinical research, supply chain, and commercial datasets with sub-second analytical querying; (2) Informatica-to-PySpark ETL Modernization: Migrated and refactored legacy batch ETL workflows into cloud-native Spark pipelines, eliminating expensive recurring Informatica licensing fees; (3) Azure Synapse & ADLS Gen2 Analytics Hub: Deployed an automated, governed data pipeline framework using Azure Data Factory, ADLS Gen2, and Synapse Analytics, establishing an auditable single source of truth for global healthcare analytics.

Core Technologies & Infrastructure Stack

DatabricksPySparkDelta LakeADLS Gen2Azure Data FactoryAzure SynapsePythonSQL

Measurable Business Outcomes

Eliminated legacy ETL licensing overhead through cloud-native PySpark pipelines

Unified multi-source clinical, supply chain, and commercial telemetry in a single Delta Lake

Accelerated complex analytical query performance to sub-second response times

Delivered three successive high-trust engagements on schedule and within budget

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