Jobs in Singapore: "How I moved from investment banking to helping companies manage data, analytics and AI solutions"

Raela Wang is the Asia-Pacific & Japan (APJ) Director of Field Engineering at US tech company Databricks, which has its regional headquarters in Singapore. Databricks is also working with IMDA and its training partners to upskill over 10,000 individuals in data and AI.
 

1) Tell us about what Databricks does, its customers and your role there.

Databricks is a global data and AI company that helps organisations unify and simplify their data and AI landscape so they can make informed business decisions and innovate faster. We do this through our Data Intelligence Platform which brings together data, analytics, and AI in a centralised, open, and secure solution. This breaks down silos, fosters collaboration across teams, and accelerates the development and deployment of data-driven solutions for our customers. With support for diverse data sources, open-source technologies, strong governance, and multi-cloud integration, our platform helps organisations realise the full potential of their data and AI investments. These organisations include global brands like Adobe, Heineken, MasterCard, Shell, and Prada Group, as well as local names like GovTech and CPF Board.

At Databricks, I lead the early career programme across Asia-Pacific and Japan. My role centres around enabling and supporting our early career hires as they grow from solution engineers to customer-facing solution architects. In Databricks, solution architects act as trusted advisors to our customers. They work closely with organisations to understand their data challenges and design solutions on the Databricks Data Intelligence Platform. By combining deep technical expertise with business acumen, solution architects help customers adopt best practices in data engineering, analytics, machine learning, and AI to unlock the full value of their data. In terms of support, I help these junior hires acquire the necessary technical and soft skills, as well as pre-sales expertise to thrive in their roles.
 

2) You graduated with a Bachelor of Arts degree, but have since gone on to pursue data science and AI. How have your professional interests evolved over the years to lead you to where you are now at Databricks?

My career started in finance and later took me to the Swiss investment bank Credit Suisse, where I often automated daily tasks with Excel macros. Over time, I got bored with the repetitive nature of the work and wanted to explore more efficient ways to automate these processes. That’s how I first got into programming. Over time, my interest grew, and I eventually left banking to pursue it more seriously. As I had no tech background and minimal work experience in this field, I enrolled in a data science night course for working professionals in Silicon Valley. In the day, I volunteered at various tech startups in the San Francisco Bay Area to gain exposure to data challenges. After completing the night course, I applied to hundreds of companies, and ultimately joined Databricks in 2015.

Looking back on my career transition, I would say luck has certainly played a role, as I’ve been privileged to meet the right people at the right time, especially in 2014 and 2015 when I first stepped into the field of data science and AI. That said, I also believe strongly in the value of hard work, taking calculated risks, and creating opportunities for yourself, which were what ultimately helped me succeed in this completely new arena. And then there’s grit — I sent out hundreds of resumes, and didn’t give up even after being rejected multiple times for not having a relevant Bachelor’s degree in tech. I persevered, kept building my portfolio, and worked on my technical skills.
 

3) You’ve spent almost a decade of your professional career at Databricks, in San Francisco, London, and now, Singapore. What has it been like growing alongside the company?

I am proud to have joined Databricks as their 60th employee, and have since had the unique opportunity to witness its incredible growth to more than 8,000 employees worldwide today. My career with Databricks has taken me from San Francisco to London, and eventually back to Singapore in 2021. I moved to London when the company was seeking to expand its presence in Europe, the Middle East, and Africa (EMEA), and found ourselves operating out of a small, shared working space that seated only a handful of us. What followed was a whirlwind of customer meetings, community engagements at events, and interviewing at scale to assemble a team capable of serving the fast-growing demand for data and AI across the region.

In 2021, I joined the Singapore team to help replicate that playbook for APAC as our business was just starting to ramp up in the region following the establishment of the APJ headquarters here in December 2018. These international moves weren't initially part of my plan, but as Databricks experienced exponential growth, new opportunities within the company naturally emerged.

I would say living and working abroad have made me independent from a young age. More importantly, it has exposed me to diverse cultures and mindsets, broadening my worldview beyond what I learnt growing up here in Singapore. Working in the San Francisco office at Databricks gave me the opportunity to work with the best engineering talent globally and learn from charismatic and inspiring leaders. These experiences motivated me to raise my own standards in terms of my professional goals and who I aspire to be.
 

4) Having worked in tech companies overseas, what do you think are some of the life skills one needs to stay relevant in global organisations? What advice do you have for others on navigating through an AI-driven world?

One important lesson I’ve learnt is that speaking up does make a difference. Someone I worked with in the US very early on at Databricks once told me, “Closed mouths don’t get fed.” That phrase really resonated with me because it made me realise that while it’s good to work hard, doing so quietly won’t get you very far — you have to make sure your voice is heard as well. Be an advocate for yourself and ask for opportunities. Visibility of your work is so important.

AI has definitely left an impact on the job market, but I see great opportunities for those who are willing to embrace it. For instance, AI has made vibe coding possible — users can now use GenAI coding assistants to rapidly generate code using natural language. While this has reduced the demand for software engineers who write perfect lines of code, we still need skilled humans to interpret and review the AI-generated code to ensure it makes sense.

To remain relevant in the field of data science and AI, staying curious is key. I think it's important to constantly question how things work and to actively experiment with new emerging technologies hands-on. The best approach is to leverage AI as a tool to drive efficiency. Use AI to learn faster, upskill quickly, and focus your time on creative problem-solving. The learning journey doesn’t end with landing the role — it’s about continuous learning and growth.