Latest / The Comeback Career Podcast with Fexingo: Returning After a Gap, Stay-at-Home Re-Entry / How a Career Gap Helped One Parent Return as a Data Analyst
Transcript
- Lucas: So we get a lot of questions from listeners who've been out of the workforce for five, seven, even ten years, and they worry that the skills they had are just... gone. Obsolete. And I think today's story is a really good counterargument to that. Luna: I love a good counterargument. Who are we talking about? Lucas: Maria Santos. She's a mom of three in Phoenix, former elementary school teacher. She stepped away from teaching in 2019 when her second child was born, and then her third came along, and suddenly it was 2026 and she'd been out for seven years. Luna: Seven years. That's a big gap. And she went back as a data analyst? Lucas: Yes. At a regional health system in Arizona. Hybrid schedule, two days in the office, three at home. Starting salary sixty-two thousand dollars — which is actually five thousand more than she was making as a teacher when she left. Luna: That's impressive. And honestly, a lot of people in her position would think data analytics requires a computer science degree. Lucas: Right, and she had zero coding background. But she found a path that didn't require a four-year degree or even a bootcamp. And we should say — a quick honest thing here. This show is completely ad-free, and a small group of listeners keeps it going through buy me a coffee dot com slash fexingo. That support lets us spend time finding stories like Maria's. Luna: Yeah, it really does. And we appreciate that. So Maria — how did she start? Lucas: She started with a free SQL course on Khan Academy, just to see if she even liked working with data. Then she moved to a more structured program through a nonprofit called Career Forward — they offered a twelve-week community college certificate in data analytics for two hundred dollars. Luna: Two hundred bucks. That's affordable. What did it cover? Lucas: SQL, Excel pivot tables, basic statistics, and Tableau for visualization. No Python, no machine learning. Just the core tools that a lot of entry-level analyst roles actually use day to day. Maria told me she spent about ten hours a week on it, mostly after the kids went to bed. Luna: That's doable. But the certificate alone — does that get you hired? Lucas: It gets you past some HR filters, but Maria knew she needed a portfolio project. So she found public data from the city of Phoenix on home sales and property taxes, cleaned it up in Excel, built a Tableau dashboard showing which neighborhoods had the biggest price increases over five years, and wrote a short summary of her findings. Luna: That's smart. It shows she can take raw data and tell a story. And it's locally relevant — a Phoenix employer would care about that. Lucas: Exactly. She put the project on a simple Google Sites page, linked it on her LinkedIn, and then started doing informational interviews. Not asking for jobs — asking people in data roles what their day looked like, what tools they used, what they wished they'd learned earlier. Luna: How many of those did she do? Lucas: About fifteen over two months. The sixteenth was with a senior analyst at Southwest Health Partners in Phoenix. They talked for forty-five minutes, and near the end he said, 'We're actually hiring an entry-level analyst. Would you be open to applying?' Luna: That's the dream scenario from an informational interview. So she applied — how did she handle the gap question? Lucas: She told me she practiced a specific framing. She said, 'I spent the last seven years managing a complex household budget and scheduling logistics for four people across school, activities, and medical appointments. That taught me prioritization, attention to detail, and how to communicate across different stakeholders.' She didn't apologize for the gap. She translated it. Luna: That's a much better answer than 'I stayed home with my kids.' And it's true — raising multiple kids is project management. Lucas: Right. And she backed it up with the portfolio and the certificate. So they brought her in for an interview, gave her a short SQL exercise — joining two tables and aggregating some patient visit data — and she passed. They offered her the job. Luna: Did she negotiate? I feel like a lot of returners forget they can negotiate. Lucas: She did. The initial offer was sixty thousand. She asked for sixty-two, pointing out that her Tableau skills would let them reduce their reliance on an outside contractor who was billing them seventy-five an hour. They came back with sixty-two and a flexible schedule — two days in office, three at home. Luna: Good for her. And that flexibility is probably essential with three kids. Lucas: Exactly. She told me that the hybrid schedule was actually the bigger win than the two thousand dollars. She can pick up her youngest from preschool at three thirty, then log back on after bedtime. That kind of arrangement wouldn't have been possible in teaching. Luna: It's a totally different career structure. One thing I love about this story is that she didn't need to learn Python or become a data engineer. She found the entry-level niche that actually hires people with her background. Lucas: Right. The Bureau of Labor Statistics projects about twenty-two percent growth for data analyst roles through 2033. And a lot of those openings are in healthcare, government, and insurance — industries that are often more open to non-traditional backgrounds than big tech. Luna: So for someone listening who's been home for five or six years and thinking about data, what's the one concrete step they should take this week? Lucas: Maria's advice: take the free SQL course on Khan Academy or SQLZoo — it's like three hours total. If you enjoy the logic puzzles, then invest in a low-cost certificate. Don't go straight for a ten thousand dollar bootcamp. And do one portfolio project using data from your own city or hobby. Luna: And start those informational interviews early. You don't need to know everything before you talk to someone. Lucas: Exactly. Maria said the interviews also helped her realize she wasn't as rusty as she thought. Just talking about data with professionals rebuilt her confidence. And that confidence came through in the actual interview. Luna: I think that's the hidden benefit of the whole process — you're not just learning SQL, you're re-learning how to talk about yourself as a professional. Lucas: Yeah. And she's been in the role for about four months now. She said the first month was overwhelming — there's always a learning curve with domain-specific data — but by month three she was leading a small project analyzing patient no-show rates. Luna: Wow. That's real impact. And she's doing it without a computer science degree, without a bootcamp, and after seven years out. Lucas: Right. So if you're listening and you've been hesitating because you think the gap is too long or you don't have the right background — Maria's story is a pretty solid counterargument. Luna: It really is. And we'll link to the Career Forward program and the free SQL resources in our show notes. Lucas: Next week we're talking to a listener who returned as a supply chain coordinator after a six-year gap. That one's interesting because she had zero logistics experience. Luna: I'm curious how she pulled that off. See you then. Lucas: Take care, everyone.