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Python Software Engineer - 31024
Outside of work, I enjoy exploring new technologies, solving puzzles, and learning about different fields beyond software development. I have a curious mindset and like challenging myself with side projects, whether it’s automating small tasks or experimenting with new programming concepts. In my free time, I also enjoy movies, gaming, and spending time outdoors. I appreciate a good balance between deep focus on work and unwinding with hobbies that keep me creative and motivated.
Remote
Technologies: Python • Pandas • gRPC • Azure • Docker
The core objective is to automate repetitive daily tasks for customers by creating a framework of their routine work. This is achieved by recording their activities and converting them into robot-executable processes. The main role was aggregating streams of data about executed actions and transforming them into programmable actions. Tools used include Python3, gRPC, pandas, and OpenCV. Processed data is stored in an in-house relational SQL database. Led the project to refactor legacy codebase, reducing technical debt and improving code maintainability. Team consisted of a total 15 people, including 10 developers, PO, scrum master and test team of 3.
Main achievement:
- Successfully refactored the system from the ground up, boosting execution speed by 3x.
- Many peer-to-peer and knowledge share sessions to have same expertice level across the team.
Technologies: Apache Spark • Python • Azure Data Factory • SQL
Main focus was to migrate a core monolith application from on-premise to Azure Cloud, divide it into microservices and align security measures for handling sensitive medical report data. Such tools as PySpark, Azure, SQL Server were used. Processed data is stored in an in-house relational SQL database, later migrated to Azure SQL DB instances.
- Migrated data processing jobs from on-premise to Azure Cloud using Azure Data Factory and PySpark.
- Utilized Azure Data Factory for complex data workflows, ensuring seamless integration across systems.
- Implemented cloud architecture best practices, reducing cloud costs by 17%.
- Optimized PySpark jobs, implementing python and pyspark best practices
Technologies: Python 3 • Django • Docker Compose • Algorithm • PostgreSQL
Developed a movie information system using Python 3, Django REST Framework (DRF), and Docker. Optimized query performance for handling large datasets. Implemented a tree structure for quick movie name suggestions, enhancing user experience. Used Pandas for fast ETL processes, enabling efficient data processing, selection, and grouping.