This week I sat down with one of our Data Schoolers, who is about to finish up his time with us. In this conversation, Tim went through his background prior to joining, his experience during the program and his advice for potential applicants.
Tim has had a diverse career path in marketing and property development and most recently as a backend software developer in Melbourne. During this time Tim worked with Java and Ruby. His interest in data analytics is relatively recent and arose in part from a desire for a role with more emphasis on communication of technical knowledge and to present and discuss ideas with clients and collaborators. Tim enjoys playing basketball competitively/socially and exploring Sydney’s many nearby coastlines. His favourite meal is Chicago deep-dish pizza.
1. What was your background before joining the Data School?
Before joining the Data School, I had a varied background. My most recent role was as a Junior Software Engineer, which I found quite dry and lacking in human interaction. Prior to that, I had my own business in property and real estate in Melbourne, and had also worked in marketing. I was interested in staying within the tech industry but wanted a role that would allow for more business interaction and problem-solving, which led me to research data analyst and business analyst positions. The Data School’s program and application process appealed to me, as it seemed to offer a more practical and creative approach compared to a traditional job application.
2. Can you describe a typical day during the initial four-month training period?
The training program had a structured approach, with periods of focus on specific tools and skills, such as Tableau, Alteryx, SQL, and data modeling. Typical days would involve a mix of interactive lectures, where the cohort would learn new concepts, and hands-on lab sessions, where we could apply what we had learned under the guidance of the instructors. The program was designed to be practical, encouraging us to dive in and learn on the go, rather than aiming for perfection before attempting to implement solutions.
3. How did the training program prepare you for working with clients?
The training program instilled in me a sense of confidence and problem-solving skills that helped me transition into the client work phase. I learned how to quickly adapt to new challenges and not be afraid to dive in, even if I didn’t have a complete understanding of the problem. The program also taught me to take a more consultative approach, where I could provide recommendations and push back when necessary, rather than just delivering what the client requested.
4. Can you describe a memorable project or piece of work you’re proud of?
One of the most memorable projects for me was when I had the opportunity to be the team lead on a project. This allowed me to see the bigger picture and work collaboratively with my team members, guiding and assisting them as needed. I found this experience very rewarding, as it gave me a deeper understanding of how the different components of a data project come together and the importance of effective teamwork and communication.
5. How has the support from mentors, colleagues, and coaches been throughout the program?
The support has been great, and I’ve experienced it in two key ways. First, if I’m stuck on a data problem, I can reach out to my cohort, teachers, or the broader support network. It’s helpful to get a fresh perspective or a quick win to move forward. Second, the support extends beyond technical challenges—it’s also about building confidence. Teachers like Bethany have been fantastic at easing imposter syndrome and offering encouragement when needed. That combination of technical guidance and emotional support has been a really positive aspect of my experience.
6. How has that confidence grown as you’ve worked with stakeholders?
I’ve gained the confidence to acknowledge when I’m unsure about something, which might sound paradoxical, but it’s been empowering. Rather than fumbling through and worrying about being questioned on my skills, I’ve learned to be clear about what I can deliver and what’s realistically possible. This has also helped me adopt a more consulting-focused approach—pushing back when needed, instead of just providing the answer the client might expect. I now feel more assured in trusting my training, experience, and judgment, which has been a valuable shift in how I approach challenges and conversations with stakeholders.
7. How has the Data School program helped you launch your career in data?
The program has been an excellent foundation, giving me the skills and confidence to thrive in the broader data world and job market. Coming from an agency deeply embedded in this field, I feel assured that the training aligns with industry demands and project expectations. It’s also been valuable to experience the consultancy side of data work, collaborating with diverse clients and gaining insights into varied business environments. Additionally, the program fosters a strong network of peers, trainers, and mentors, which has been invaluable for support and professional connections as I grow in this field.
8. What advice would you give to someone considering applying to The Data School?
Take the time to dive into some research. There’s a wealth of resources online—YouTube has great content on what it’s like to work as a data analyst or consultant, and platforms like Tableau Public can really spark creativity and inspiration. Similarly, Alteryx challenges are a great way to get hands-on experience and understand the types of problems you might encounter in the field. It’s also worth reflecting on your own strengths, weaknesses, likes, and dislikes since data analytics is such a broad field and can offer something for everyone
