Chişinău, Chișinău, Moldova
I'm a Certified AWS Python developer with working knowledge of JavaScript, always eager to explore new technologies and improve my skills. I enjoy solving problems, building clean and efficient solutions, and collaborating with others to bring ideas to life. Curious by nature and proactive by mindset, I thrive in environments where learning is continuous and creativity is encouraged. Whether it's web development, desktop apps, or data-related projects, I bring enthusiasm, adaptability, and a strong sense of responsibility to everything I do.Technical skills: Front-end: React | Vue3.js (Composition API) | HTML5 | CSS | Tailwind Back-End: Flask Web Framework | FastAPI | RESTful API | Postman | JSON | Gunicron | OpenAPI/Swagger Data engineering & Automation: Selenium (Python) | ETL pipelines | Beautiful soup | Requests | Apache Airflow | automated DAG generation Data Analysis & Visualization: NumPy | Pandas | Matplotlib | Seaborn | OpenCV | Vizro Databases: PostgreSQL | SQLLite3 | MongoDB | Redis DevOps & Tooling: Git | Github | AWS | Docker | GitHub Actions Languages known: Python 3 | SQL | JavaScript Testing: Pytest | Unittest Operating systems: Windows | Linux (Ubuntu)
• Migrated over 110 real-time scripts from PHP to Python within three months, improving average response time by approximately 25% and reducing connectionrelated errors by 40%. • Enhanced the real-time data collection framework by expanding supported sources, increasing overall data coverage by 30% while maintaining ingestion stability. • Standardized data formats before ingestion, reducing downstream transformation inconsistencies by 20% and improving overall data quality across pipelines. • Optimized end-to-end ETL workflows, decreasing preprocessing time by 20% through improved validation and structured data enforcement. • Designed and implemented a usage monitoring tool to analyze service consumption patterns, providing visibility into traffic spikes and operational load distribution, enabling faster anomaly detection and reducing incident response time. • Introduced a propagated exclusion list mechanism to filter banned providers at the earliest stage of the pipeline, preventing non-compliant data from entering preprocessing workflows and reducing invalid data ingestion by 25%. • Reduced unnecessary preprocessing overhead by approximately 15% by implementing upstream filtering logic, improving efficiency of ingestion pipelines. • Implemented schema validation mechanisms prior to database insertion, reducing malformed records in production datasets by 40%. • Designed an automated Airflow DAG generation system from templates, reducing manual workflow setup time by 60% and ensuring standardized pipeline structure. • Maintained high code reliability through unit and integration testing, achieving stable production deployments with minimal rollback incidents. • Authored technical documentation outlining data contracts, operational workflows, and governance processes, improving onboarding efficiency and cross-team alignment.
• Developed web applications using Flask/Django • Created automation scripts to streamline data processing tasks • Built RESTful APIs for web applications. • Designed and implemented database schemas for Flask applications. • Integrated third-party services and APIs into existing projects • Automated repetitive tasks such as data scraping, data analysis, and reporting