Data engineers are responsible for designing, constructing, and maintaining the infrastructure and systems that facilitate the collection, storage, and analysis of data. By utilizing a range of tools and techniques, they ensure that data is accessible, reliable, and primed for analysis. Their foundational work empowers companies to gain a competitive edge by deeply understanding consumer behavior, market trends, and overall business performance.
To chat about the profession, we meet with Miroslav Dimitrov. He is a Senior Data Engineer
at The Coca-Cola Company and a guest-lecturer in the upcoming Upskill Data Engineer program.
My first encounter with data was during my internship at Philips while finishing my master's degree. I had to create a data model to predict when healthy household members would have good or poor sleep. The study involved collecting data from sensor devices placed on the participants and in their homes. The data was in raw form, and I had to group it into event logs, based on which I trained and tested the model. After completing the project, I wanted to continue working with data and started my first job in the field at Coca-Cola Bulgaria LLC. Initially, I focused on building visualization reports for bottlers and gradually delved into adding functionalities to the backend data platform. This is how my passion for data engineering was born, and it’s what I continue to do to this day.
For the past four years, I have been working on developing new functionalities for a Financial Data Product. The business requirements for the data I receive are dynamic, necessitating the continuous addition of new features and ongoing optimization of the product.
My greatest achievement in the field involves migrating one of the company's legacy ETL tools from on-premise to the cloud. The ETL process was built in Informatica, and the goal was to migrate it to the Azure Cloud environment, specifically to Synapse Analytics. The aim of the migration was to reduce the costs associated with maintaining Informatica licenses and to eliminate the complexity of maintaining additional tools in the data platform. My task was to reverse engineer the file conversion process and rewrite it in Python using Synapse notebooks. Achieving this goal resulted in a 30% reduction in file processing time.
In the Upskill Data Engineer program, I focused on the SQL Advanced topic. I chose this topic because I believe SQL is one of the leading programming languages in the field and a key discipline for capturing the interest of anyone who wants to pursue data engineering. Additionally, this topic is foundational for continuous growth and development in the field.
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