Models fail quietly when yesterday’s file never landed. Lunai’s data engineering practice builds the pipes: ingest, validate, store, serve — with logs you can read at 2 a.m.
Platforms and patterns
We pick warehouse vs lakehouse vs operational store based on latency and skill on your team, not on a vendor keynote.
- Batch and near-real-time ingest from ERP, IoT, apps and files
- Incremental loads, SCD and slowly-changing reference data
- Tests on row counts, nulls, referential integrity and drift
- Cost controls on Azure, AWS or on-prem SQL you already own
Built for Indian ops
Financial year, GSTIN, plant codes, and files that arrive late on festival weeks are first-class concerns, not afterthoughts.
- Idempotent jobs you can rerun without double-counting
- PII handling and access reviews
- Handover so your internal engineer is not stranded
Hire Lunai for data engineering in New Delhi when you are tired of “the dashboard looks fine” while the warehouse is empty.