Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!
A bit about Nasia:
Nasia Ntalla is an Analytics Leader and Tech Lead who sits at the intersection of data, leadership, and human development. With over 10 years of experience at Meta and in fintech, she has built and scaled modern data platforms, led teams through 0–1 product journeys, and driven “Data as a Product” transformations.
What sets her apart is her dual background in engineering and transformational coaching. Nasia not only designs data systems but also helps people thrive within them – coaching engineers through career pivots, leadership growth, and burnout recovery. She is particularly interested in AI-native data workflows, data culture, and building organisations where both data and people can do their best work.
How did you start out in your tech career?
I studied Mechanical Engineering, but by the time I graduated, I realized I had no interest in traditional engineering roles. However, I knew I loved mathematics and finding patterns. While working as a university researcher, I started applying for jobs in Berlin and came across a role at Delivery Hero titled “Junior Business Intelligence Analyst.” Even though I didn’t fully understand the title at the time, it sounded intriguing and I had some basic SQL knowledge from my research. I actually ended up learning more SQL and developing a deeper understanding of the product during the interview process itself, which launched my career in data.
What are the signs of success in your field?
Success means different things to everyone. For me, it isn’t about titles; it’s about trust and impact. I feel successful when I am a trusted partner in my workplace, when I can see the tangible impact of my insights on the company’s direction, and when I am able to add real value to my team’s daily operations.
What is the best and worst thing about your job role?
The Best: I love uncovering hidden patterns and gaining deep insights into various areas of the business through data. It feels like solving a puzzle every day.
The Worst: Occasionally, I have to spend a lot of time explaining why data is important and why we should be data-driven, even when it feels like it should be completely obvious!
What can you advise someone just starting out to be successful?
Be deeply curious and take the time to truly learn your product. Tech is so much broader than just writing code or querying databases; it’s ultimately about finding the right opportunities to make the world a bit easier and more efficient for people.
How do you switch off?
I catch up with friends, go out, travel, and spend time acting- which is a huge passion of mine!
What advice would you give your younger self?
Be bold and don’t hesitate to share your opinion. I would also remind myself that just because some people speak loudly and confidently, it doesn’t mean they know more than you do. Often, they’ve just mastered the art of being vocal. Trust your knowledge.
What is next for you?
Career-wise, I want to keep solving complex problems, educating teams, and guiding companies on their data journeys. Looking ahead, I really want to spread my knowledge further, mentor others, and give back to the tech ecosystem.
If you could do anything now, career-wise or personally what would you do? Why?
I would love to use my skills to tackle some of the global challenges we are facing today. Times feel heavy right now, and it seems like major decisions aren’t always made with the best intentions for humanity or the environment. I’d love to help bring back a bit of that human focus and support environmental sustainability.
What are your top 5 predictions in tech for the next 5 years?
- The AI Plateau: We will see a massive initial acceleration of AI-driven products, but this will eventually slow down as companies realize that keeping up requires more resources and infrastructure than they possess.
- Integration into Daily Life: AI and automated systems will shift away from being “hype” and quietly become embedded in our daily workflows and routines, reaching a steady, normalized state.
- Green Tech Prioritization: As data centers and AI models consume massive amounts of energy, the tech industry will be forced to pivot sharply toward sustainable infrastructure and energy-efficient computing.
- The Rise of Tech Literacy Outside of Engineering: As “no-code” and data tools become standard, non-technical roles will require a much higher baseline of data and tech literacy to function.
- A Return to Human-Centric Design: After the initial rush to automate everything, there will be a strong counter-movement prioritizing human connection, ethics, and empathy in product development.
Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!
Want to become a DSF Speaker? Apply here!