Almudena Sanz Olivé advice for other women in tech? Find what motivates you

Before coming to Elastic, Almudena Sanz Olivé was the only woman on her team at her first data science job.

“I joined with a group of people and some people treated me a bit differently. It was the first time I was like, ‘Hey, what’s happening?,’” she says. 

While she’d been the minority before, this was the first time it was noticeable, Almudena says. 

“This has never happened to me again. When I’ve had to hire people, I see more and more CVs from women.”

Almudena grew up around female role models who worked in tech or tech-adjacent fields. Her mom is a civil engineer and many of her aunts and uncles are also in engineering. So, Almudena was used to seeing women in tech roles. 

At seven years old, Almudena built her first website with her dad’s help. She would also regularly go to her grandparents house and rebuild electronics in their garage. On top of that, her dad, a math teacher, gave her math problems to solve. 

“I feel like it came naturally to me to solve these problems and think about things this way,” she says. “You see patterns and you come up with ways to solve them.”

That way of thinking would come in handy later in her career as a data scientist, but Almudena first went to school for electronics engineering, which she describes as a mix of electric engineering and computer science.

“When I had to choose a degree, my family asked me what I was thinking of pursuing. They asked if I had considered engineering because I’m good at cracking problems and I like tech a lot,” Almudena says. “They [my family] gave me the idea to go into engineering. When someone tells you it’s a possibility, it’s easier to consider it.” 

During her junior year, she studied aboard in California and took one of their artificial intelligence courses. 

“I thought that [AI] was interesting as well,” Almudena says. “It gave me a foundation, I studied a lot of stats, math, and data.”

Now, Almudena is a principal data scientist working on Elastic’s observability analytics team. 

“We make sense of the telemetry data that our customers use,” she says. “We collect that and we use data engineering processes to shape it into a way that we can use it and make sense from it.”

This includes building dashboards for models and working with internal stakeholders to understand how the product is being used.

“A big part of data science is explaining complex things,” Almudena says. “You have to be able to communicate well — that’s one of the most critical skills. You have to be able to explain things and be a teacher. I really enjoy that part of it.”

Almudena has also had the opportunity to work with the AI assistant team to build a framework to understand how Elastic customers are using AI assistants and evaluate the quality and accuracy of AI. 

“I love tools that help people understand their data. We use ML and AI in the background so people can better understand their data.” 

Almudena found the part of tech she really loved. For others interested in joining the tech industry, she recommends finding what motivates you. 

“Tech is just a tool. It’s the means to an end. Figure out what motivates you to find answers for people. Find what gives you energy and take that path,” she says. 

There are many ways to get to what motivates you, she says. Almudena’s first jobs weren’t in data science — she moved into the field later in her career because it’s what interests her the most. 

For women specifically, Almudena wants women to do what feels natural to them. 

“There are many ways to add value,” she says. “Do what feels natural to you. I’m a bit more observant, I like to observe and then add more once I see the dynamics. You don’t have to be anyone else. Just be yourself.” 

She also recommends finding mentors like she had growing up. 

“Find people that you relate to. Find a mentor and a support system.”

Interested in a career in tech? Check out open roles.