Machine learning is already helping enterprises predict equipment failures, identify fraudulent transactions, forecast demand, and improve operational decisions. But developing a machine learning model is only the beginning. The bigger challenge is keeping that model accurate, reliable, and useful as business…
Data Lakehouse Engineering
Unified storage and compute for analytics, ML, and AI on a single foundation.
We design and implement lakehouses on Databricks, Delta Lake, Apache Iceberg, and Snowflake that serve analytics, ML, and operational workloads from one platform without trading off governance or performance.
- Medallion architecture, Bronze, Silver, and Gold tiers, with clean lineage from raw ingestion to business-ready data
- Delta Lake and Apache Iceberg implementation with ACID transactions, time travel, schema evolution, and unified batch and streaming access
- Databricks Lakehouse platform deployment with MLflow, Unity Catalog, and feature store integration on a single workspace
- Open table format migration from proprietary formats to Iceberg or Delta for full vendor portability and future flexibility
- Lakehouse governance with Unity Catalog, column-level security, row-level filtering, and end-to-end data lineage
- Hybrid lakehouse deployments balancing cloud storage economics with high-performance query engines for mixed workloads
