Originally from Ireland, Trea is a Neuroscience graduate from the University of St Andrews, where during her studies she was introduced to data analysis and its powerful capacity to communicate information. Throughout her final year when she focused on researching neurodegenerative disease and potential therapeutics, she experienced firsthand the utility of data analysis as it took her research from masses of unclear and messy data to clear, succinct, and easily communicable insights.
Following this she sought out opportunities to further explore this field, dabbling in some python and R, and she was led to the Data School.
Trea spent her first and second placement at IAG Cargo, where she worked extensively with SQL in both Snowflake and Oracle to efficiently prepare, transform, and optimise large datasets. Leveraging Tableau alongside this, she tailored dynamic reports to varied business requirements, presenting intricate data in visually compelling formats.
For her third placement, Trea joined Cordavis, a biosimilars company, where she took on a range of Data & Analytics responsibilities. This included managing relationships with third-party vendors and collaborating with data architects and engineers to understand the end-to-end data acquisition and pipeline processes involved in setting up data analytics and warehousing for a growing company in the pharmaceutical industry. Her hands-on exposure to data pipelines encouraged an interest in pursuing data engineering, leading her to apply for the for the first cohort of the TIL Data Engineering School.
Since starting the TIL Data Engineering School, Trea has been working on developing her skills in building data pipelines, working with cloud platforms, and mastering tools like SQL, Python, and Airflow.
When not working with data, Trea enjoys more creative endeavours such as baking and anything vaguely crafty - from crochet to watercolours.