Our screening process
What “pre-screened” actually means
Most staffing companies say their candidates are pre-screened. Very few say what that involves. Here is ours.
Screening is run by someone who works in the discipline being hired for — not by a recruiter reading a keyword list. What gets checked changes with the role, because a data engineer and a cloud engineer are not strong at the same things.
Every role
Six things we confirm before a profile reaches you
These run on every candidate whatever the discipline. Ask us to show any of them for anyone we put forward and we will.
Role and requirement alignment
Before we look at anyone, we agree what the role actually needs - the stack, the seniority, what the person will own, and which requirements are firm rather than nice to have.
Experience review
We read the history against your requirement: what they built, at what scale, how recently, and whether the environment resembles yours.
Role-specific technical discussion
A conversation, not an exam. Someone who works in the discipline goes through the areas the role depends on and how the candidate has handled them in production.
Communication assessment
Whether they can explain a technical decision to someone who did not make it. On augmentation roles especially, this is what decides whether a placement works.
Availability and engagement preference
Start date, notice period, and whether the engagement model you are offering is one they actually want. Confirmed before anyone reaches your shortlist.
Client-ready profile
We write up what we found - strengths against your requirement, and anything worth knowing - so your hiring manager reads reasoning rather than a resume.
By discipline
What the technical discussion covers
The stages above are the same for everyone. What gets discussed inside the technical conversation is not — these are three of the disciplines we place into most often.
Data Engineer
- SQL depth
- Python and PySpark
- ETL/ELT design
- Cloud data platforms
- Data modeling
- Orchestration
- Troubleshooting pipelines in production
Cloud Engineer
- Cloud architecture
- Networking
- Infrastructure automation
- Security and access
- Deployment
- Day-two operations
AI / ML Engineer
- Python
- Model development
- ML pipelines
- Deployment
- MLOps
- Model evaluation
- AI running in production rather than in notebooks
Being straight about it
What our screening is, and what it is not
Screening is a practitioner conversation and a written write-up. It is deliberately ordinary, and we would rather say so than imply an apparatus that does not exist.
What it is
- A technical conversation led by someone who works in the discipline
- Checked against your requirement, not against a generic checklist
- Written up so your hiring manager reads reasoning, not a resume
What it is not
- A proprietary assessment platform or a scoring model
- A timed test, a take-home exercise, or a certification check
- A substitute for your own interview — it is what makes yours worth running
Tell us the role, we’ll bring the shortlist
Send us the requirement and we’ll come back with who we’d put forward, what we checked, and how quickly they can start.