How to start a career in data (The View on Data, Ep.1)

The debut episode of View on Data brings together its five co-hosts, Grace Goheen, Lauren Benezra, Faith Lierheimer, Paige Berry, and Erica Louie, for an honest, often hilarious conversation about building a career in data.

This monthly roundtable series is hosted by women in data and tech, and it’s all about sharing candid career stories, lessons learned, and the unfiltered reality of working in this industry. Each episode is part storytelling, part advice, and part “you had to be there” banter.

In this first conversation, the hosts swap tales about unconventional career pivots, surprising opportunities, and the skills that really make a difference.

Please reach out at podcast@dbtlabs.com for questions, comments, and guest suggestions.

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Many paths lead to data careers

One of the biggest takeaways from the episode is that there’s no single “right” way into data. Everyone’s journey looked different:

• Grace Goheen studied industrial engineering and dabbled in theater before a senior-year Python and R course sparked her interest. After joining a consulting company during the pandemic, she completed an internal SQL and dbt bootcamp and started working on internal data projects. She kept a “venting journal” of product frustrations and ideas, which ended up helping her move into product management.
• Lauren Benezra began as a “snobby pure math person,” moved into applied math, learned to code, and worked with lab robots before discovering the joy of cleaning messy data. “It’s the thing that makes my brain tingle,” she said.
• Faith Lierheimer worked in animal behavior research, including catching crickets in Hawaii with a headlamp, and in science education before pivoting during the pandemic through a bootcamp. “I was basically Fivetran-ing my crickets into Excel,” she joked.
• Paige Berry majored in art, worked in coffee shops, and discovered Excel in an office job, which led to a 21-year career in analytics. She’s also the creator of custom Slack emojis used across the company. “Every time I see one pop up, I get a little dopamine hit.”
• Erica Louie studied political science and Italian, learned VLOOKUP on YouTube, and cold-emailed dbt Labs’ founders. “They said ‘wear whatever you want’ to the interview, so I showed up in cut-off shorts and a zip-up hoodie.”

Excel is often the starting point

A recurring theme was how many careers started with Excel.

“Excel is a gateway drug,” Erica said. “You think it’s just a spreadsheet, and then next thing you know, you’re building dashboards.”

For many, Excel was the first time they saw they could manipulate data, find insights, and solve problems, and that spark eventually led to SQL, BI tools, and dbt.

Soft skills are power skills

While technical skills matter, the group agreed that communication, adaptability, and collaboration are just as important.

“Knowing how to be a decent human at work is a skill, and it’s actually harder to find in data than you’d think,” Lauren said.

These skills can make or break a project, and they often determine whether you’re trusted to lead initiatives or interface with stakeholders.

How to stand out in interviews

The panel shared practical ways to make an impression when applying for data roles:

• Do your homework. “If you’re applying to dbt and you bring up the roadmap post in your interview,” Grace said, “I’m impressed. It means you cared enough to look.”
• Follow up. Paige told interviewers, “I don’t know, but I can learn”, and then followed up later with researched answers.
• Show adaptability. Employers value people who can step into unfamiliar territory and figure things out.
• Highlight collaboration. Data is rarely a solo activity. Demonstrating teamwork is a big plus.

Mentorship accelerates growth

Mentorship came up repeatedly as a career accelerator. Sometimes it was a formal program; other times, it was simply shadowing someone on a project.

“Getting to be a fly on the wall was huge for me,” Grace said about shadowing a product manager before officially moving into the role.

Erica compared approaching a potential mentor to dating: “You don’t just say, ‘be my mentor.’ You start with a conversation.”

Advice for breaking into data in 2025

The group acknowledged that entering the field now is more competitive, but far from impossible. Their advice:

• Build a strong network, especially in communities like the dbt Community Slack.
• Keep your goals short-term. Focus on your next step, not your five-year plan.
• Say yes to unusual or unexpected projects; they can open unexpected doors.
• Keep learning and share your work publicly to build credibility.

“Don’t think five years ahead,” Erica said. “Think one year ahead. You change too much in this industry to plan farther than that.”

Why there’s no one path into a data career

There’s no single formula for breaking into data. Whether your background is in math, art, science, or something else entirely, curiosity, persistence, and a willingness to keep learning can take you far.

Sharing stories like these helps break down the gatekeeping that can make data roles feel inaccessible and reminds us that there’s space for many different kinds of practitioners in the field.