Data Platform Engineering
A foundation your analysts trust.
Most organisations are running analytics on brittle, manually maintained data pipelines that nobody fully trusts — the result is duplicate reports, contradictory numbers and strategic decisions based on incomplete data. Migradia designs and builds modern data lakehouses, real-time streaming pipelines and governed semantic layers that give your analysts and data scientists a reliable, auditable foundation. We partner with your data team throughout the build, embedding good engineering practices and leaving you with a platform your team owns and can extend.
- Lakehouse architecture (Delta Lake / Apache Iceberg)
- Streaming pipelines (Kafka / Pulsar / Amazon Kinesis)
- Data transformation & orchestration (dbt / Apache Airflow)
- Semantic layer & metrics store
- Data governance, cataloguing & lineage
- Self-serve analytics enablement & training
We assess your data estate — quality, governance, lineage and architecture — before designing any analytics or AI capability.
Lakehouse or warehouse architecture designed for your workload, compliance requirements and team capability.
Ingestion, transformation, modelling and serving layers built, tested and documented by our data engineering team.
Training, documentation and a structured handover programme. Your team operates the platform independently after engagement.
Pipeline reliability improved from 82% to 99.6%
Analyst self-serve adoption reached 70% within 90 days
Regulatory reporting automated end-to-end
Get a scoped 30-minute consultation. We map your scenario and propose a clear delivery plan — no commitment required.
Book a consultation