Building A Data Team - Who To Hire First?

How do I start a data team? Who should I hire first? Common questions for small and medium organisations looking to leverage their data.

New leaders in the data space will likely be measured on how quickly they can deliver beneficial insights to the organisation, insights which typically need to lead to financial improvements. Of course, doing things properly takes time, a new cloud data platform which automates data ingestion and processing, and spits out polished analytics is a big undertaking. Therefore, who you hire first can have a big impact on success in your role.

A number of articles and posts I've read recently suggest you should carefully pick a specific role to start your data function.

• "Start with an architect as a well designed data platform will save you time and money in the long run"
• "Pick a data engineer because they can start building right away and can actually build unlike architects"
• "How about a data analyst as they can do a bit of everything"

The "what role" question isn't the right one as it ignores some important context. The important questions being:

How much is your organisation is willing to invest in data?

Here are a few options to consider as you build your team.

Small Investment - An onshore team

For those with a small budget, hiring a few employees with multi-faceted skill sets may well be the right option, they can jump in at the deep end designing and building. However, the results will likely be a bit rough around the edges and wont have a lot of the extras you'd like to expect. User experience, data governance and other important considerations are typically lacking.

Call them data analysts or whatever you like, they'll need to be capable in each fundamental data domain - architecture, engineering and analytics (among others!). If not they'll need to be able to learn as they go, researching and experimenting constantly.

These people (the good ones!) are typically expensive, in demand and wont be easy to recruit. It will take time to find them and get them onboard. They'll also need a strong data leader to direct them and ensure their work is structured and focused on delivering value, a Project Manager or IT leader wont do. Getting your data strategy right and making sure its actionable with a small team is essential.

My goal in this situation would be to deliver visible and measurable results early in order to secure funding to recruit a broader set of dedicated roles (Architects, engineers, scientists...). At the same time aiming to minimise technical debt and other issues that arise from the initial employees skillsets being overly stretched.

Small Investment - An Onshore & Offshore blend

Alternatively, focusing on offshore development while keeping business engagement onshore can be a great method to keep costs low and increase development capacity.

The trick being to find the right partner to support you, as launching your own offshore development centre is a big undertaking. Instead partners in this space with pre-existing development centres will recruit, equip and manage technical resources on your behalf at a low cost.

This leaves your small onshore team able to focus on the human aspects of data - strategy, governance, ways of working, literacy, ethics...

Large Investment

If you've got significant investment don't do it yourself. Identify what you want to achieve via a data strategy and then pay someone else to do it.

Instead of spending significant time and money recruiting a multifaceted data team, while delivering minimal results, leverage an organisation which already has lots of these people and can spin up projects on a few weeks notice.

Of course using an external organisation like a consultancy comes with a high cost, make sure you do your due diligence and check they:

• Have supported organisations like yours through the same journey several times over.
• Actually have the people and skills they claim, and that they're available to you specifically.
• Have strong methodologies, tooling and accelerators to deliver value quickly.

While they build the platform, recruit your permanent team in parallel and have the consultancy train your new employees as they're onboarded. Aim to become self-sustainable as soon as possible to minimise costs.

Conclusion

Too many organisations try to cut corners as they grow, hiring small teams of data analysts and working through trial and error. There are a number of ways to be successful but regardless of the method building a successful data function costs money and often quite a lot of it.

Securing proper investment into people and not just technology is required for success.