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IT Outsourcing
Data, analytics and AI engineers who join your team and work in your repositories, tickets and stand-ups, while our architects review their merge requests.
When teams bring us in
This model fits when you own the roadmap and need more people, or a skill your team doesn’t have yet, to deliver it.
The roadmap is set, but hiring senior data engineers locally is slow and expensive.
We propose engineers matched to your stack and your seniority bar. You interview them and decide who joins.
Your team knows the business but has never built on Databricks, dbt or an LLM stack.
An engineer who has built on them joins the team, works on real tickets and pairs with your people, so the skill stays after they leave.
The last contractors left code nobody wants to touch.
A DATAI architect reviews every merge request from our engineers against your conventions, on top of your own review.
One project needs a small team for a while, not permanent hires.
A squad with its own lead engineer takes a defined piece of your backlog and hands it back tested and documented.
Ways to add engineers
Two ways to staff the work, and one review standard behind both. The services overview compares this with a project team.
Dedicated engineers
One or more engineers working full time in your team, on your backlog and in your ceremonies, managed day to day by your lead.
You receive
- Engineers matched to your stack
- Named accounts in your systems
- A DATAI lead who checks in with you
Squads for projects
A small team led by a DATAI engineer that delivers an agreed piece of work inside your process and tools.
You receive
- One lead engineer as your contact
- Weekly demo of the work
- Handover notes for each piece
Senior code review
A DATAI architect reviews our engineers’ merge requests for design, tests and security, and raises risks with your lead early.
You receive
- Review on every merge request
- Notes on recurring issues
Roles we staff
Each role works in the tools below. Tell us your stack and we match engineers to it.
Listing a technology does not imply a vendor partnership or certification.
Data engineer
- Apache Airflow
- Apache Spark
- Apache Kafka
- dbt
Analytics engineer
- dbt
- Power BI
- Looker
- Tableau
AI and LLM engineer
- OpenAI
- Anthropic Claude
- LangGraph
- Langfuse
ML engineer
- MLflow
- SageMaker
- Databricks Mosaic AI
- Weights & Biases
Cloud and platform engineer
- Terraform
- Kubernetes
- GitHub Actions
How engineers join your team
Our usual four steps, with matching in place of the assessment, and a fifth for when the team needs to change.
Our delivery standard- 1Call30 minutes with a senior engineer on the gap in your team you need filled.
- 2MatchingWe send profiles of engineers who fit your requirements. You interview the ones you shortlist and choose.
- 3OnboardingWe sign an NDA first. Then each engineer gets a named account through your identity system, access to your repositories and a first ticket.
- 4WorkingEngineers join your stand-ups and reviews. A DATAI architect reviews their merge requests, and a DATAI lead checks in with you on how it is going.
- 5Changing the teamAdd people, swap a skill or wind down on the notice agreed in the contract, with open work handed over.
How a squad works, written down
The way a squad works is agreed in writing before anyone starts: who leads it, where it works, who reviews the code and how the team changes.
An illustrative example, not client data.
Questions about IT outsourcing
Not answered here? Ask in the request form.
Can we interview the engineers first?
Yes. You see their profiles, interview the people you shortlist and decide who joins.
Who owns the code they write?
You do. They work in your repositories under accounts you control, and the work belongs to you, as the contract sets out.
What if an engineer isn’t the right fit?
Tell your DATAI lead. We go through what is missing with you and agree the change, whether that is a different engineer or a different mix of skills.
Request engineers
Tell us the roles and the stack you need.