Practice · Data Engineering
Data platforms built by certified senior engineers
Lakehouse architectures, streaming pipelines and warehouse migrations on AWS and Azure — Snowflake- and Databricks-certified engineers who have moved enterprise data estates to the cloud.
100+engineers on staff
72%Senior / Lead level
5.6%attrition — industry low
~2 wksto a productive engineer
What we staff
The modern data stack, end to end
Databricks & Snowflake — certified engineers; lakehouse design, Unity Catalog, cost-aware workspace architecture.
Spark at scale — batch and streaming processing, bronze/silver/gold layering, performance tuning.
Orchestration & ELT — Airflow, dbt, Kestra; tested, versioned, documented pipelines.
Streaming — Kafka and cloud-native messaging (AWS MSK, Azure Event Hubs) for real-time platforms.
Warehouse migrations — SQL Server, Oracle and Hadoop estates moved to cloud lakehouse architectures.
BI & serving — Power BI dashboards and data marts your analysts can actually use.
Proof
Data platforms in production
TelecomAnalyticsglobal telecom analytics platform delivered
RetailReal-time CDPstreaming customer data platform on AWS — Kafka, Redshift, dbt
MigrationSQL → Lakehouseenterprise DWH moved to Hadoop & AWS Databricks
Profile examples
Who you'll work with
Databricks · Snowflake · Kafka
Senior+ Data Engineer
Representative profiles. Full CVs, CEFR levels and current availability on request.
How it works
From brief to a productive engineer
48 h
First CVs
Pre-vetted, from the bench.
2–5 d
Full shortlist
Bench roles; sourced: 2–3 weeks.
Your call
Interview
You assess and decide.
~2 wks
Productive
DM-led onboarding.
Send us one data role today.
First pre-vetted CVs within 48 hours — and a productive engineer in ~2 weeks.