Position: Data Engineer
Category: Python
English level: intermediate
Years of experience: 1

Data Archiving Strategy:
Accomplishment: Developed a data archiving strategy using Python and SQL to move historical data from the primary database to a low-cost storage solution. This optimized the primary database's performance and reduced storage costs, resulting in 20% savings in infrastructure expenses.
Automated Data Testing Suite:
Accomplishment: Designed and implemented an automated data testing suite using Python's testing frameworks. The suite included unit tests and integration tests for data pipelines, ensuring the accuracy and integrity of data transformations. As a result, data-related issues were detected early in the development process, reducing the number of production incidents by 20%.
Automation and Scripting: Python is frequently used for automating repetitive tasks and writing scripts for system administration.
Data Analysis and Data Science: Python's libraries such as NumPy, Pandas, and Matplotlib facilitate data manipulation, analysis, and visualization.
System Administration: Linux administrators manage servers, configure networks, and ensure system security and stability.