Starting Point: My First Steps in Tech

My journey began with a curiosity about how data shapes decisions in today’s world. During my internship, I had the opportunity to explore core concepts like working with databases, cleaning data, and understanding how different systems communicate. This laid a strong foundation for my future work.

Some of the key skills I picked up during this phase include:

Writing SQL queries to manipulate and analyze data.
Setting up and managing Azure cloud services, including virtual machines and serverless databases.
Using Docker to containerize applications and ensure communication between services.

The Internship: Real-World Learning

As an intern, I got hands-on experience working on real-world projects. One of my key responsibilities was managing and cleaning datasets to ensure they were ready for analysis. This involved:

Parsing and organizing data to make it actionable.
Removing duplicates and handling missing values.
Splitting columns to better structure the information.

I also worked on automating processes, which taught me how to optimize workflows for efficiency. Tools like Azure, Power BI and SQL Server became essential in my day-to-day tasks.

Overcoming Challenges

No journey is without hurdles. Some of the challenges I had to learn from are:

Cloud Management: Setting up a virtual network in Azure required learning about security configurations and monitoring tools.
Data Visualization: While Power BI looks user-friendly, it took time to learn how to effectively represent complex datasets without overwhelming the audience and build informative graphs.
Communication skills: At first, it was difficult to ask questions because I was afraid they might sound stupid. However, don’t wait for others to speak up on your behalf. Take the initiative to ask your questions and propose solutions if no one else does.
Storytelling skills: You must know how to explain technical concepts to non-technical people. At the end of my internship, we had a meeting with the entire department, including people from HR and other non-technical teams. They don’t necessarily understand technical terms, like a 'database schema' or 'API endpoint.' It’s important to break down these ideas in simple, relatable terms so everyone can follow along and understand your work.

I overcame these challenges by breaking down problems into smaller, manageable tasks and continuously seeking feedback from mentors.

Transitioning to an Associate Role

After months of hard work, I was offered a part-time position as an Associate Data Engineer. This transition was possible because I focused on building practical skills and demonstrating my ability to solve problems. Key areas that helped me stand out include:

My proficiency in SQL, especially in tasks like cleaning and transforming data.
My ability to work with cloud platforms like Azure to build and manage infrastructure for databases.
My understanding of how to present insights using tools like Power BI.

Advice for Aspiring Data Engineers

If you’re looking to break into data engineering, here are some tips based on my experience:

Learn the Fundamentals: Master SQL and basic data cleaning techniques.
Explore Cloud Platforms: Familiarize yourself with cloud concepts. You could learn Azure or AWS. Cloud computing is a significant part of modern data engineering.
Build Projects: Work on projects to show and improve your skills. These can be solo projects or team efforts. Don’t just stick to simple ideas like making a “to-do list” app. Try something new, like working with cloud technology or AI. It’s okay if the project isn’t perfect. What matters most is what you learn from it.
Seek Feedback: Don’t hesitate to ask for guidance from mentors or peers. During my internship, I wrote down my questions in a document for every meeting to make sure I didn’t miss anything. Even if you think you know the answer, it’s a good idea to confirm with your mentors—it’s a great way to get feedback and learn.
Stay Curious: The tech world evolves too fast. Keep learning about new tools, frameworks, and best practices.

Final Thoughts