Data Platform Engineering

Build Data Platforms That Scale

We design and build production data platforms grounded in real engineering patterns we’ve deployed across banking, manufacturing, FMCG, and financial services.

Every platform starts with a clear medallion architecture — bronze for raw ingestion, silver for validated and conformed data, gold for business-ready analytics. But the real value is in the details: how CDC streams are handled, how data quality rules are enforced, and how the platform scales as new data sources are added.

What We Deliver

Architecture Design — We define the platform blueprint: compute topology, storage layout, ingestion patterns, and data flow. This isn’t a slide deck — it’s a working architecture document with Terraform modules and pipeline templates.

Pipeline Development — Production ETL/ELT pipelines with proper error handling, checkpointing, idempotency, and monitoring. We build pipelines that operations teams can actually maintain.

Streaming & CDC — Real-time ingestion from Kafka, Event Hubs, and database CDC streams. We’ve built Kafka CDC pipelines from SQL Server through Confluent Cloud into Delta Lake medallion layers for regulated banking environments.

Data Quality — Config-driven DQ engines that validate data at ingestion with quarantine tables for failed records. Non-engineers can manage rules without code changes.

How We Work

Engagements start with a platform assessment — we review your current state, identify gaps, and produce a prioritized roadmap. Implementation follows fixed-scope phases with defined deliverables. You get a working platform, not a consulting report.