AI projects stall on data far more often than on models. A good data engineer gets the data clean, current and in one place, so dashboards agree with each other and models have something solid to learn from. That is the work our data engineers do.
Tell us what you want to build. A senior engineer sends back a scope and a fixed price within two business days, no obligation.
The role
Skills
Process
Tell us the stack, the problem and how you want to work. We confirm fit on a short call.
We send profiles of pre-vetted senior engineers who match your stack and domain. You interview and choose.
Your engineers onboard and start delivering without a long recruiting cycle, with working software at the end of each sprint.
Engagement models
Add one or two senior engineers to your existing team to close a specific skill gap. Your leads, our specialists.
A small senior team working only on your roadmap, with a lead who owns delivery.
A scoped build such as a RAG system, a model or a pipeline, delivered to an agreed outcome.
Related work
Next step
Comparing options? Read what it costs to hire AI developers or contact us to discuss your project.
FAQ
Snowflake, Databricks, BigQuery, Redshift and Postgres, plus orchestration with Airflow and modelling with dbt. We work with what you have unless there is a strong reason to change.
Yes. Migrations from stored procedures and legacy ETL tools are common work, done in stages with results compared at each step.
Yes. Building clean datasets and feature tables for ML teams is a big part of the job.
With automated checks on freshness, volume and values in the pipeline itself, so problems are caught before anyone sees a wrong number.
Yes. Engagements can be a defined project, someone embedded in your team, or a small dedicated team.
Keep reading
Indicative ranges only get you so far. Tell us the specifics and get a scope and a fixed price in two business days.