Data in the UK is a big industry – ironically little data exists to tell exactly how big, but as I write this in November 2025 itjobswatch.co.uk lists just under 4000 open jobs requiring SQL skills, and over 5000 requiring Python skills. The UK’s largest data conference, ‘Big Data London’ had over 15,000 attendees in 2025.

Trying to plan your career in data is tricky. What industry should you work in? What technologies are the best to get experience with? How do you keep up in an industry that changes every year?

One key question we all face is how much to specialise. What does being a specialist look like on a day to day basis? Do you work on the same projects as a specialist?

I can’t pretend to know all the answers – but I did want to share my experiences following a recent career change.

Previously I worked for a large enterprise, where I rotated through a number of teams of specialists – each having in-depth knowledge of a specific domain and the technologies in it. Whereas Powerverse’s data team is quite small, and our strategy involves working as generalists – we all have to do some of the above.

Job titles change constantly, but when I worked at an enterprise, some of the below job titles were used in the business for specialists.

• Data Analyst
• Data Scientist
• Data Engineer
• Business Intelligence
• AI Engineer
• MLOps Engineer
• Devops Engineer
• Data Architect

The work done by most of the roles above still exists within Powerverse in some form.

Our day to day includes:

– Dashboards to build for our business partners (like a BI professional)

– Models to build (Data Science) and models to deploy (MLOps) for our intelligent scheduling service

– A data warehouse to design (Data Architect) and data pipelines to build (Data Engineering) to serve clean, well structured data to all our data products

In spite of the requirements being similar, being a generalist still feels quite different. Here’s a few reasons why!

More independence

When you specialise, you rely more heavily on your co-workers to support you. Most data products require several specialists working together to deliver. For example, a dashboard might require a data engineer and a BI professional to work together.  As much as I like my colleagues – coordinating together takes time and effort – i.e. more meetings. As a generalist I spend more time writing code, and less time explaining to other people what I’ve done.

Diagnosing bugs is easier (but fixing them is harder)

As a specialist working with other specialists, *triaging* bugs becomes harder. A common scenario is that a key reporting figure becomes inconsistent with other sources of truth. This could be caused by the report itself, by a data engineering pipeline serving the report, or by software, e.g. an API or a model generating the raw data. Trying to track down exactly where the bug is can be hard when no individual has a joined up picture of the system end-to-end.

However, just because it’s easier to diagnose a bug as a generalist – doesn’t mean fixing it is easier! Working across many systems I sometimes feel that I lack the depth of knowledge that is helpful to fix a tricky bug in a specific area.

Thinking more like a businessperson

Being able to build and run all the parts of a product has also given me a more joined up view of the whole system and the users it serves. As I’m able to deliver complete products by myself, I also get a complete list of all the requirements from our business leads. This also means I’m able to make some small product decisions myself. By contrast – a team of multiple specialists may only get a small part of a product to deliver each, and lack perspective on how it all fits together.

Smaller products

Big, complex, products with many users need lots of people to build them. The complexity makes it impossible for one person to know everything, so some degree of specialism is essential when building larger systems. Smaller products only require a smaller team or an individual to build – but that individual has to be broader and more flexible.

So which is better? There’s no right answer! The world needs both generalists and specialists. 

If it’s very important to you personally to have more ownership or work independently, being a generalist might work well for you, but that might not be the case for everyone.

If you’re struggling to decide which direction to take your career – the quality of the projects and teams you work on matters much more than the number of hats you’re expected to wear! 

Written by Robert Carter, Data Engineer at Powerverse