The foundation everything else rests on.
Lakehouse architecture, streaming, transformation, quality, observability — modern data engineering that makes analytics and AI tractable.
Modern data, modernly engineered.
Lakehouse architectures, ELT-first transformation, streaming where real-time matters, data contracts where reliability matters. We build the foundation analytics and ML rest on.
Six capabilities. One operating system.
Lakehouse Architecture
Iceberg / Delta / Hudi on object storage, queryable from every engine.
Ingestion
Fivetran / Airbyte / custom CDC, streaming via Kafka / Kinesis / PubSub.
Transformation
dbt-first ELT, with tests, lineage and documentation.
Data Quality
Great Expectations / Soda / dbt tests with SLA-grade enforcement.
Observability
Lineage, freshness, volume, anomaly detection across the stack.
Data Contracts
Producer-side contracts for critical tables — break the upstream, not the downstream.
From kickoff to compounding outcomes.
Audit
Current state, debt inventory, critical-path analysis.
Architect
Target architecture aligned with cloud, scale and team.
Build
Lakehouse, ingestion, transformation, quality, observability.
Migrate
Move critical workloads with parallel running and validation.
Operate
SLA-grade operations, ongoing optimization, evolution.
Where this earns its keep.
Modern data stack migration
Move from legacy DW / ETL to lakehouse + ELT, with measurable cost and velocity gains.
Real-time data
Stream-first pipelines for fraud, personalization, observability and operational use cases.
Data quality programs
End-to-end quality tests, data contracts and SLAs for the tables your business depends on.
Cost optimization
Warehouse query patterns, storage strategies and engine selection that cut cloud spend 40%+.
Frequently asked
Modernize your data foundation.
A 60-minute audit of your current data stack, critical-path bottlenecks, and the highest-leverage modernization moves.