I am a Data Analyst with over four years of experience working in a multinational environment, where I focus on transforming complex datasets into clear, actionable insights that support informed business decision-making. My role combines strong analytical expertise with modern reporting, automation, and cloud-based technologies.
I have a solid technical background in Microsoft Excel, SQL, and Python, with hands-on experience using Pandas, NumPy, and Matplotlib for data preparation, transformation, and analysis. A core part of my work involves developing and maintaining dashboards in Google Data Studio, Excel, and Power BI, ensuring stakeholders have access to accurate, reliable, and easy-to-understand performance metrics.
In addition to reporting, I use Python to automate and optimize data preparation workflows that feed scheduled reports, improving efficiency, consistency, and data quality. I also regularly execute and optimize SQL queries to extract and process large volumes of data from multiple sources, focusing on performance, scalability, and maintainability.
Beyond traditional analytics, I work on enhancing and developing cloud-deployed AI solutions, with a strong focus on scalability, performance, and data-driven capabilities. This allows me to contribute not only to analytical insights but also to the continuous improvement of intelligent, production-level systems.
To support my cloud and analytics work, I hold both the Microsoft Azure Fundamentals and AWS Certified Cloud Practitioner certifications. I am currently preparing for the AWS Certified Solutions Architect – Associate certification and am also considering pursuing the AWS Certified Data Engineer certification to further strengthen my expertise in cloud architecture and data engineering.
I am detail-oriented, technically driven, and motivated by solving data challenges end to end—from raw data extraction to insight delivery and intelligent automation—while continuously expanding my skill set to deliver measurable business value.