Reinventing a Career in Tech | Xia He-Bleinagel

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Alexey: Hi everyone, welcome to our event. This event is brought to you by Data Dogs Club, a community of people who love data. We have weekly events, and you can find more details in the link in the description. Subscribe to our YouTube channel to get notified about all future events. We also have an amazing Slack community where you can interact with other data enthusiasts and ask questions. (0.0)

Alexey: During today's interview, you can ask any question through the pinned link in the live chat, and we will cover them during the session. I used to use Grammarly but stopped a while ago. There’s a meetup in Berlin about how Grammarly uses LLMs, which sounds interesting. Now that the intro is done, I have the questions file ready. If you're ready, we can start. (36.0)

Alexey: By the way, you have very nice earrings. (1:25)

Xia: Thank you. (1:30)

Alexey: This week we'll talk about career transitions, leadership, and building inclusive data teams. We have a very special guest today. Xia is the head of data and cloud at NOV, a German company supporting the transition to zero-emission mobility through data and cloud innovation. Her journey from being a full-time mom to leading a data team is a story of resilience, growth, and inclusion. Welcome to our event. (1:36)

Xia: Thank you, Alexey. I’m happy to be here. (2:22)

Alexey: We have interacted before, including during your courses and a recent lunch. It’s very pleasant to have you here. I want to start with your background. Can you tell us about your career journey so far? (2:27)

Xia: Sure. I studied automotive engineering in China, Italy, and France. Moving to Germany was never part of my plan. I had the chance to study at TU Munich but declined because it was too cold. I studied in Lyon, which was very nice, and later moved to Berlin when my husband relocated. (2:54)

Xia: It was very difficult to find a good job in the automotive industry in Berlin. I got married and had two children, so I spent four to five years at home. I tried one job that was not relevant to my studies, just to get back into work. In 2018, I decided to study data science and become a data scientist. (3:39)

Xia: I pursued a second master’s in data science at HTW Berlin. I changed jobs frequently, almost every year, until I found my current role at NOV, which I find meaningful. The company culture is excellent, and I’m very motivated. I was promoted in a very short time. (4:25)

Alexey: You’ve been doing data science since 2018, so roughly seven years. That’s quite a lot. (5:11)

Alexey: Do you remember the times before AI, when everything had to be done manually? (5:30)

Xia: Yes. It was difficult, especially with two children and a completely different background. (5:37)

Alexey: Can you tell us more about what you studied to make this transition? You mentioned a master’s, but it must have been challenging. (5:49)

Xia: The turning point came unexpectedly. A British headhunter called me and asked if I knew machine learning. They were looking for someone with a mechanical engineering background for a robotics startup. I had never heard of machine learning or reinforcement learning before. (6:03)

Xia: I had spent so much time with my children that I felt out of society. I decided I wanted to do something for myself and took action. I found a master’s program at HTW Berlin, which focused on data science project management, combining R, statistics, and advanced data analysis. (6:45)

Xia: I was not fully satisfied, as it didn’t make me a data scientist at that time. I also took many courses in Coursera, including Andrew Ng’s deep learning specialization, which inspired me. I gained broad knowledge of machine learning and deep learning. (7:33)

Alexey: I also started with Andrew Ng’s courses. They have grown into a specialization now. (8:15)

Alexey: Did you ever use R outside your studies? (8:39)

Xia: No, not really. I had an internship that required Python, which I was not familiar with. It was a very challenging experience. (8:44)

Alexey: Finding your first internship and job must have been difficult, especially with two children. How did your previous background help? (9:17)

Xia: It was challenging. I partly got the internship because of my automotive engineering background. The consultants needed someone with that experience, so I had a practical advantage. Andrew Ng’s courses helped me a lot, especially for practical interview questions. (9:46)

Alexey: So your previous experience helped you get started, similar to my own experience transitioning from Java development. (10:38)

Xia: Yes, every experience helps. Even the unrelated jobs I had while raising my children helped me meet university requirements. I always try to learn something from every experience. (11:18)

Alexey: What did you do as an import expert? (12:11)

Xia: I bought and exported German goods to China via online platforms and imported Chinese goods to Germany. (12:21)

Alexey: So they needed someone who spoke both Chinese and German. (12:33)

Xia: Yes, exactly. (12:40)

Alexey: Even if it wasn’t related to your ultimate goal, it helped you get started. (12:45)

Xia: Yes, it was challenging in the beginning, but I made the best out of it. (12:50)

Alexey: At some point, you came across our courses and Zoom Camps. Can you tell us how that happened? (13:01)

Xia: I took many courses on Coursera, Udemy, and other platforms. They were mostly theoretical but gave me broad knowledge. I followed your courses at the very beginning during COVID when I was home with two children. (13:12)

Xia: I completed two Zoom Camps: Data Engineering and MLOps. Both were challenging and helpful. I had to use Docker, Terraform, and cloud tools, which was overwhelming at first. The second camp was easier. (13:47)

Xia: I built an automatic end-to-end data pipeline with a nice CO2 dashboard. These skills helped me in interviews and at work. I credit these courses for helping me land two jobs. (14:35)

Alexey: You mentioned your first and second jobs after the courses. What helped you the most from these courses? Was it the projects, the skills you gained, or something else? (15:00)

Xia: I think the design of the courses is excellent. They focus on real use cases we see in daily work. The instructors are professionals from other companies and bring their perspectives into the courses. The final projects let you combine everything you learned to build a portfolio. For interviews, this shows if a person is motivated and can work independently. (15:18)

Alexey: You have two kids, worked, and took these challenging courses. How did you manage your time, especially with module one of the Data Engineering course? (16:10)

Xia: Module one turned out to be very difficult, even though I expected it to be easy. At the time, my kids were in kindergarten, and I had a job. From 9:00 p.m. to midnight every day, I spent two to three hours learning and doing projects. I was very curious and absorbed knowledge like a sponge. I even explored web development and AI EOS development to understand how things work, even if it wasn’t directly related to data science. (16:42)

Alexey: That’s impressive. Learning web development helps even when you don’t need to code daily, especially for understanding code generated by AI tools. (18:51)

Alexey: You mentioned that these courses helped you land two jobs. Can you tell us more about the first and second ones? (19:45)

Xia: The first job was as an AI and data consultant in a big consulting company. The interview focused on machine learning, so I reviewed the machine learning Zoom Camp to refresh concepts, which helped me present well. The second job was as a data engineer at NOV. I benefited a lot from the courses since our tech stack included AWS, Docker, and Terraform. (20:10)

Alexey: You started at NOW as a data engineer. Now you are head of data and cloud. How did that transition happen? (21:16)

Xia: It wasn’t planned. I am spontaneous and don’t plan my life years ahead. I started as a data engineer, imagining I could grow into a senior role and mentor juniors. The real trigger was a company working group for data science. (21:49)

Xia: The group allowed data people across teams to exchange knowledge and attend events. I wanted to contribute to the community, so I took responsibility for initiatives, such as AWS certification sprints and promoting diversity. These efforts gave me more impact and satisfaction beyond technical work. (22:31)

Xia: Later, the head of data left, leaving a big gap. I stepped in because I had the most knowledge of AWS. I continued my daily work while taking on these responsibilities. (25:01)

Alexey: When I transitioned from senior to tech leadership, I couldn’t maintain my previous workload. Did you manage both your daily work and these new responsibilities simultaneously? (26:00)

Xia: Yes, I didn’t manage people at first but took over coordination and technical responsibilities from the other team. Later, as head of data, I focus on team building and strategic planning. (26:28)

Alexey: How does your day look now? (27:36)

Xia: It’s very busy. I joined three months ago and focused on team building, introducing new structures and routines, prioritizing projects, and addressing backlogs. I also focus on innovative projects for the future and securing budget and resources. (27:45)

Alexey: How did you learn to handle all these responsibilities in the first 100 days? What resources helped you? (28:57)

Xia: I learned a lot from my previous team and team lead. Observing how they worked gave me a role model. I could adopt their methods rather than starting from scratch. The strong team spirit made the transition smoother. (29:30)

Xia: I didn't start from zero. I immediately booked a coaching course, which helped me because leadership is like a new language or a new field. There are frameworks and tools, and no one is born a leader. If you are interested in people and can reflect, you can be a good leader. (30:16)

Xia: In terms of resources, I took a course from the Hula Academy, which I can recommend. The trainer was really nice and it helped me reflect and gave practical tools. The second resource is the book How to Win Friends and Influence People. It's a classic book that gives general guidance on interacting with people. (30:54)

Xia: There’s also a movie called How to Lose Friends and Alienate People. It's a dark English comedy. I never managed to finish the book How to Win Friends and Influence People; I tried multiple times. I read it on a long trip to Canada while staying in an Airbnb. Some ideas in the book are reasonable but challenging to implement. (32:22)

Alexey: I see a few questions from the audience. One person asks about transitioning back to data and AI after time in management. Do you have recommendations for them? (33:28)

Xia: This is something I have thought about. I enjoy programming and solving complex problems, but as a head of data, I don’t have much time for hands-on work. I thought I could spend 20% of my time coding, but that was naive. Before this interview, I did some Terraform refactoring with a colleague. (33:57)

Xia: My suggestion is to talk with your manager if the culture is open and supportive. It’s good to explore and see if it fits. If not, it’s okay to change. In my last company, Elix, we had two career tracks: individual contributor and management. (34:48)

Xia: In the individual contributor track, there are technical leadership roles like staff or principal engineer. In management, roles include manager, head of data, or engineering manager. Lateral moves are possible. For example, a head of data could transition to a principal engineer role to be more hands-on. The reverse is also possible. (35:37)

Xia: Career transitions depend on the company. If the structure is clear, it’s easier to move between technical and management tracks. (37:16)

Alexey: I also want to plug our courses. In January, we start the data engineering course. Tomorrow we start AI Dev Tools for Zoom Camp, showing how to use tools like CoSora and GitHub Copilot to be a more effective engineer. (37:33)

Xia: I registered but haven’t had time yet. I tested AI tools for prototyping my website. As a former manager, I noticed my developer skills were getting rusty. These tools help me be productive again, almost like when I was an individual contributor. (38:18)

Alexey: Another question is from Rupa, who has six years of experience and is learning German. They want a job in Germany. Any advice for international hiring? (39:33)

Xia: I can’t recommend specific companies. Learning German is very important. The job market is competitive, but big international companies do hire. Some positions require B2 German level. Knowing German helped me get my first job in Germany. (39:59)

Xia: Focusing on German companies reduces competition. At Elix, when we opened a position, there could be 100 applications in minutes. Most applicants weren’t qualified. Targeting German-speaking companies gives you a better chance. (41:23)

Alexey: I shared a link to your careers page. Rupa has B2 German, which is enough to work. (42:30)

Alexey: How did you learn German, and what’s your recommendation for people in Berlin? (43:00)

Xia: I started with intensive courses. After seven or eight years, I spoke German every day but with poor grammar. Last year, I retook a one-year individual course in Berlin, which helped a lot. Depending on your level, you can do intensive daily lessons or focus on specific areas. (43:06)

Xia: I took morning classes at Deutsche Academy near Alexanderplatz, which was convenient. Evening classes didn’t work for me because my brain was tired after work. Morning classes allowed me to study German and still have time for other activities. (44:04)

Xia: At that time, I was at home and could focus on German and driving lessons. Morning classes helped allocate my time effectively, especially when I was managing my own schedule. (45:09)

Xia: Sometimes I didn’t have to work 40 hours a week; I could allow myself to work less. Other times I worked more, but as my own boss, I could manage my time. In a regular company, it’s a bit more difficult. (45:36)

Alexey: How would you recommend starting a career in cloud and data? (45:48)

Xia: I recommend taking courses and building projects. For example, the Data Engineering Zoom Camp covers all the technology we use daily. Write Terraform code and build projects. For consultants, certifications can also open doors, even though it’s a lot of theory. (45:58)

Xia: I never formally took AWS certification, but preparing for it helped me understand IAM roles, which were confusing at first. Similarly with German, I prepared for the B1/B2 certificate, which improved my language skills even though I didn’t care about the certificate itself. (47:08)

Xia: Setting goals and deadlines helps. For example, I set a deadline for the German certificate and prepared seriously for it. Having a deadline forces commitment and makes a big difference. (48:38)

Alexey: Next time, we could do a podcast in German. (49:52)

Xia: Small talk is the most I can do now. If I were forced to work in German, I’d improve quickly. I do use German more often than English, especially in my current company, which pushed me to practice. (49:59)

Alexey: We didn’t cover inclusion and mentorship. You have experience as a mom of two. Do you mentor other women in similar situations? (50:35)

Xia: Yes. I had to figure out most things on my own. My husband didn’t know anything about data, and I had no network. Now, with a little free time, I give back. Many women I know in Germany stay at home, even with master’s or PhD degrees. I find that unfortunate. (51:06)

Alexey: Do you think this is cultural? (52:24)

Xia: Yes, partly. In China, couples often need both people working full-time. In Germany, the system allows people to work less because the financial need is lower. Married couples have tax incentives, so there’s less pressure to work. (52:29)

Xia: I want to teach my daughter to be herself. It’s especially hard for foreigners without much support. That’s why I started a working mom project in my neighborhood. We meet in local living rooms, help review CVs, and provide guidance. It’s not about doing everything for them, but sharing experiences and encouragement. (54:01)

Xia: I went back to university at 30. If I waited until 40, it might have been different. Now, I mentor two women: one is a single mom who hasn’t worked for five years, and another is a recent graduate struggling to find a first job. I want to give back because this journey is challenging, especially for foreign women. (55:27)

Alexey: Some women may be less lucky or lack access to these groups. Are there online resources or meetups you recommend? (56:35)

Xia: Pi Ladies is a good general group for women. I’ve also engaged with Women in Big Data Berlin. There’s a group for freelancers and entrepreneurs called The Wounded, which offers mentorship programs. I’m currently mentoring through them for three months. (57:01)

Alexey: I see a comment from a working mom in a Zoom Camp. She asks about non-technical backgrounds, like applied linguistics. (58:07)

Xia: It’s about finding your passion and strengths, not just following trends. Your background is always helpful. For example, someone with import/export experience applying for a data scientist role in that domain has an advantage. My technical background in Java helped me compared to most new data scientists. Even non-technical backgrounds can be leveraged in relevant domains. (58:37)

Alexey: Thanks for sharing your story. (1:00:34)

Xia: Thanks for sharing your story as a working mom with a linguistics background. I hope things work out. (1:00:42)

Alexey: It’s been a pleasure. Before this podcast, we interacted online. Thank you for sharing your story. If anyone else wants to share, please reach out—it motivates current and future students. (1:00:55)

Xia: Thank you. (1:01:40)

Alexey: Have a nice day. Being Head of Data is not just budget planning, but also strategic work with interesting projects. (1:01:48)

Xia: Yes, I’ll try. Have a nice day, and goodbye everyone. (1:01:59)