Data Engineering & Pipelines
Streaming and batch architectures — instrumented, idempotent, audit-friendly. Replacing the brittle scripts that quietly run your business.
What we do, and why.
Most production data systems are a quiet stack of cron jobs, notebooks and 'temporary' python scripts. We rebuild them as systems — declarative, tested, contracted, observable.
Whether you're moving from CSV exports to a real warehouse or scaling an event-driven pipeline to millions of messages per minute, we ship architectures that hold their shape under audit and on-call.
Idempotency is not an afterthought. Lineage is not optional. Quality SLAs are first-class. Engineers who inherit our work tell us the same thing: it's quieter at 3am.
What we deliver.
Modern data warehouse
End-to-end ELT into Snowflake, BigQuery, Databricks or Postgres — with dbt, tests and lineage from day one.
Streaming pipelines
Kafka, Pulsar or Kinesis topologies for real-time enrichment, fraud signals and operational analytics.
Data contracts & observability
Producer/consumer contracts, freshness SLAs, anomaly alerts, and dashboards that show the system's health, not just its output.
Migration & rescue
Move off legacy ETL tools or rescue brittle pipelines without halting the business.
Tools we trust.
Four phases, one rhythm.
Discover
Listen, map, name the real question.
Design
Sketch the system before we build it.
Build
Ship production work, weekly.
Scale
Hand over, harden, compound.