Hiring data people is difficult. Role definitions are blurry, the skills are genuinely technical, and most founders don't have the background to assess candidates accurately. The wrong hire is expensive — in salary, in technical debt, and in the time spent managing around their gaps.
We help founders hire the right people: writing job specs that attract the right candidates, running technical screens, advising on what combination of roles is actually needed at your stage. This isn't HR consulting. It's domain expertise applied to hiring.
This engagement is naturally positioned as a follow-on after any other project. We build the foundation, then help you hire the person who can own it.
What we deliver
Select a service area to see how we approach it.
Define the right roles and reporting lines for your data ambitions.
- 01
Map the current state: what roles exist, what's owned, and where gaps are causing friction.
- 02
Align on the data roadmap for the next 12 months and the team required to execute it.
- 03
Design the org structure: roles, reporting lines, and boundaries between engineering and analytics.
- 04
Write role definitions that are specific enough to hire against and evaluate performance on.
- 05
Document the decision rationale so future leaders understand why the structure was designed this way.
Attract and assess data talent that will raise the bar for your team.
- 01
Define the exact skills and experience the role requires — not a generic job description.
- 02
Write the job spec and sourcing strategy to attract the right calibre of candidate.
- 03
Design the interview loop and take-home assessment to evaluate what actually matters.
- 04
Run technical screens so you're not evaluating candidates on criteria you can't assess yourself.
- 05
Advise on offer structuring and help you make the final call with confidence.
Establish practices that keep your codebase maintainable as you scale.
- 01
Audit the current codebase for technical debt, inconsistent patterns, and missing documentation.
- 02
Define the standards: style guide, naming conventions, testing requirements, and PR workflow.
- 03
Set up the tooling that enforces standards automatically: linters, pre-commit hooks, CI checks.
- 04
Write the onboarding guide so new hires can get up to speed without asking basic questions.
- 05
Document the standards in a place the team will actually find and maintain them.
Give your data leaders the tools to build and retain high-performing teams.
- 01
Understand the leader's current challenges: stakeholder management, prioritisation, team development.
- 02
Build the request intake and prioritisation framework for analytical work.
- 03
Design the sprint ceremonies that work for data teams — not a copy of engineering process.
- 04
Create the career ladder and performance framework appropriate to your team's stage.
- 05
Document the playbooks in a format the leader can adapt as the team grows.
A data hire — or team — that's genuinely right for your stage. Confidence that you're not overpaying for a generalist or underpaying for a specialist.
Founders building their first data function, or scaling an existing team with new leadership needs.
We publish in-depth playbooks on data engineering best practices at handbook.bottomlinedata.co. Detailed guides related to this practice area will be linked here.
Start a conversation.
Every engagement begins with a focused discussion of your current data environment and priorities. To schedule an initial consultation, reach out directly.
Get in touch