My Story Into Data: Aoife O'Kane Hackett

“When I started working in data, I couldn't have told you what a data engineer did. I was put on the team, and I ended up really, really liking it.”

There’s an assumption that people working in data and AI have always known exactly where they were going. That somewhere along the way there was a carefully thought-out career plan, a computer science degree and a straight line into technology. In fact, that’s not the case for many.

Aoife didn’t start out with a grand plan for where her career would take her. What she did have was curiosity, an openness to opportunities and a willingness to keep learning. One opportunity led to another and, somewhere along the way, she realised she had found a career she genuinely loved, one that brought together the things she was naturally good at with the things she found most interesting.

Growing up, she loved maths. At secondary school that became a love of physics, which eventually took her to university to study astrophysics. It was there, almost as part of something else, that she first encountered Python and began doing more substantial data analysis as part of her final-year project. She enjoyed it enough to start thinking that perhaps data could offer a route forward after university, although precisely what that career might look like was far from clear.

“I went from being really unsure of what to do after graduating to starting to look into some data graduate programmes.”

She was accepted onto a general data and AI graduate programme and placed into a data engineering team. And that's where the story takes a wonderfully honest turn.

“I probably couldn't have told you what a data engineer did before being put on that team. I was just put there, but then I ended up really, really liking it. It worked out for the best for me, and I've just grown from there.”

Finding the Thing That Fits

Four years into her career in data and engineering, the connection between the child who loved maths and consultant Aoife today makes much more sense. It is the problem solving that still gets her.

She enjoys taking a problem, understanding what is really being asked, evaluating the different options and eventually finding a way through it. Consulting adds another dimension because she gets to do that alongside people who bring different experience and knowledge to the problem, learning from them and then carrying those lessons into whatever comes next.

As she puts it, there is a “social element of the problem solving”, and the variety in consulting keeps the work interesting. Different businesses bring different requirements, different desired outcomes and different contexts, even when some of the underlying technology may be familiar.

Today her work includes building and maintaining client data platforms in Databricks and creating monitoring solutions around them, and she has worked across finance, healthcare and the charity sector. On one current project, for example, her team is developing a platform for a biotechnology company that moves data from testing machines back to laboratories, with a focus on getting that information there quickly while keeping it structured, correct and visible when issues arise.

“I am constantly learning, this is important to me. In data, its not about having all the answers, but about being curious enough to keep finding the next question”.

Seeing That It's Possible

When I ask Aoife whether she sees a noticeable gender gap in data, she doesn’t hesitate.

The teams she has worked with in consulting have been predominantly male and, at times, she has been one of only a few women on the team. She's also noticed the relative lack of women in data leadership.

“I think that it is quite clear to see the representation gap, I think we have quite a long way to go, but I can see positive change happening”.

Aoife remembers being actively encouraged at school to consider technical industries and recalls initiatives aimed at encouraging girls towards data and technology beginning to emerge. For her, part of changing participation is remarkably simple: young women need to be able to see that these careers exist for them.

“It's kind of just seeing that it's possible and being told you can do it.”

It's a short observation, but perhaps one of the most important in her story. Getting women into data is only one part of changing the balance. What happens when they arrive matters too.

The Difference One Person Can Make

When Aoife joined Advancing Analytics, she had a female manager for the first time and admits that she hadn't anticipated how much of a difference that would make.

Her manager at the time became someone she could watch progress through the organisation to principal level, but it wasn't simply career progression that made an impression. Aoife talks openly about the encouragement she has had to speak up, give opinions, give and accept feedback which has consistently supported developing confidence in herself.

“I didn't really anticipate how much of a difference in having such a great female mentor would make - having someone to ensure you were happy, comfortable, and confident contributing to discussions enabled me to have confidence in myself.”

It is an interesting lesson in what inclusion can look like in practice. Sometimes it isn't a programme or a policy. Sometimes it is having someone notice, ask the question, listen and make sure your voice is in the room.

And that's something Aoife recognises in the wider culture at Advancing Analytics:

“Regardless of your level... everyone's encouraged to speak up.”

You Don't Have to Know Everything to Start

Perhaps that's why Aoife’s advice to someone considering data today isn't simply to learn as many technologies as possible.

Yes, she talks about Python, SQL and Databricks. But the capability she describes as “priceless” is critical thinking. As AI increasingly helps people produce technical outputs, she believes the important human skill is being able to judge whether that output is actually correct, whether it addresses the problem you're trying to solve, and whether you understand the underlying business or technology problem well enough to make that judgement in the first place.

Communication matters just as much. Being able to take something deeply technical and explain it simply to somebody who isn't technical isn't an add-on to expertise in Aoife’s view. It is evidence that you genuinely understand what you're talking about. And perhaps that's reassuring for someone standing on the outside of the industry looking in.

You don't need to arrive knowing everything to start your data career.

Aoife certainly didn't. She arrived through astrophysics, discovered Python, experimented with data analysis, joined a graduate programme without knowing exactly where it would take her and landed in a profession she hadn't previously considered. She found something she loved, but it was the teams around her who helped her recognise just how far she could take it.

Making the Path More Visible for the Person Behind You

Stories like Aoife’s matter. Gender parity in data and AI can sound like a huge, abstract ambition, but careers are built at a much more human level: somebody being encouraged to try something at school, somebody discovering a career they didn't know existed, somebody seeing a woman ahead of them and realising progression is possible, somebody checking that their voice is being heard.

Advancing Analytics are proud partners of Women in Data® and hope that by sharing personal stories such as Aoife’s will help pave a route for somebody considering their career options behind them because “seeing that it's possible and being told you can do it” is where a career begins.