Data Analytics Engineer with a strong analytical mindset and experience in technical customer support. Skilled in SQL, Python, Pandas, Excel, and PostgreSQL. I develop practical data projects focused on data transformation, ETL processes, and real-world business challenges.
Projects focused on SQL, Python, Pandas, and data engineering concepts. Each project is based on real-world business scenarios and covers the complete analytical workflow, from data extraction and transformation to reporting and actionable insights.
The portfolio demonstrates practical experience in working with relational databases, ETL processes, data cleaning, exploratory analysis, and business problem-solving using modern data tools.
SQL: complex queries, joins, aggregations, subqueries, and business-oriented data analysis
Python: data processing, automation, and ETL workflows
Pandas: data cleaning, transformation, merging, and exploratory analysis
PostgreSql / mySql: database design, querying, and working with relational datasets
Excel: data preparation, PivotTables, advanced formulas, and validation
Git & GitHub: version control and project documentation
I’m detail-oriented, analytical, and focused on practical problem-solving. My journey into data began with Excel and SQL and has since expanded to Python, Pandas, PostgreSQL, and ETL development. I learn best by building hands-on projects based on real-world datasets and business challenges.
Outside of data projects, I'm passionate about animal welfare and share my home with four cats.
Caring for animals has taught me patience, attention to detail, and consistency — qualities that also support my approach to working with data.