The Difficult Life of the Data Lead
Why balancing managing a team with demanding stakeholders and still being hands-on is no easy task
Working in data has never been harder. The data stack is growing more complex and expectations are higher than ever before.
However, one data role has it harder than most: The Data Lead.
People in data middle management roles often go by the name of Data Lead or Data Manager and it’s the only role where you have to balance managing a team with working as part of a leadership group and still doing hands-on work. No easy combination.
If you’re an IC (individual contributor) your job is challenging but your focus is clear. You succeed by delivering high quality analysis and data products and by working with stakeholders to make sure your work has impact1.
If you’re a Head of Data you work on a strategic level and if you’re lucky you have a seat at the top management table. Your role is difficult but your focus is also clear; build a great team around you and make sure the data team is working on the right priorities, and is set up to succeed in the future.
But if you’re a Data Lead you’ve got to do all of these at once.
As a Data Lead you have to manage your direct team. This includes dealing with performance management issues, making sure top performers are challenged and hiring the right people.
You also have to manage stakeholders who often have competing priorities and keep context on what goes on in each area where someone from your direct team is involved.
And you need to stay hands-on and be able to jump into code, build a dashboard or deliver an analysis that sets the bar for what good looks like.
This is a lot to balance.
All this combined makes the role of data middle management unique and as a data industry we haven’t figured out how to deal with this yet.
As the data IC career progression path is starting to become a viable alternative to the people management ladder, I’m starting to see more Data Leads being drawn to this. They’re still ambitious and want to progress in their careers but also want to get back to having time to focus on their craft and doing deep work.
If you look at engineering teams, many Engineering Managers have left behind most of their IC-related work. In fact, seeing an Engineering Manager push code to the production codebase is uncommon in many organisations.
Companies still need data managers so not everyone can move to the IC ladder. Some have suggested that Data Leads should operate more like Engineering Managers but I’m not so sure that’s what they want. In my experience, being hands-on is the part of the job they often enjoy the most.
A likely root cause of the issue
As data teams are getting larger the need for data middle managers will only increase and figuring out the best operating model is key. One solution is to stop expecting them to be able to do it all at once.
If the top priority is to grow the team, stakeholders shouldn’t expect the Data Lead to be as hands-on until the team has been hired.
If there’s a performance management issue and someone on the team requires a lot of attention, the hiring team should take on more of the initial candidate calls.
My take on what’s the most common root cause for the strain on data managers, is that it’s most often with stakeholders. They are not deliberately being difficult (I hope) and often have good intentions to push for their own business goals. But many stakeholders don’t know how to work with data people. In high-growth companies you often have stakeholders coming from all kinds of backgrounds. People coming from traditional companies in particular may expect the data team to operate more as a service function where the goal is to respond to ad-hoc data requests. This is a topic that I’ve seen consistently create a lot of friction.
It’s also not uncommon to see stakeholders fight for data “resources2” to be allocated to their projects, leaving the Data Lead in the difficult position of not being able to make anyone happy.
What can be done to improve this?
One problem is that many organisations don’t have a senior data person who has a seat at the top management table and can speak for data. This is unlike what you see in engineering where it would be uncommon to not have at least one senior technical person there.
Another solution is to educate stakeholders. I’ve always found it much easier to work with senior stakeholders who have a background in data. They appreciate how difficult some work can be and know when to cut corners. It may be wishful thinking that all senior leaders have a data background but data teams who don’t work as service functions are still a relatively new thing. Hopefully more stakeholders will get accustomed to how to work with data people.
I’m still waiting for someone to write the ultimate manual to stakeholders for how to work with data people.
If you’re working on this or have any experiences with this topic, I’d love to hear from you!
Read How Should Analysts spend their time if you find yourself spending your time very differently. I’ve also written about How to measure the ROI of data work
Stakeholder pro-tip: Don’t refer to data people as resources if you want to make friends with them