Data Analyst
Significant Efficiency and Accuracy Improvements through Data Management and Automation by encompassing the 40% data accuracy improvement via SQL in Michael Page, the 30% manual effort reduction through Python automation, the 15% team efficiency increase via VBA/Python at Teleperformance, and the improved data accuracy and efficiency at TACT FIRM.
Development and Implementation of Actionable Data Visualization and Reporting Tools which includes the interactive dashboards created in Power BI, Tableau, and Looker Studio across various roles, leading to improved client reporting efficiency (20% at LSC), faster decision-making (30% at HOME33), and enhanced stakeholder communication.
Driving Strategic Insights and Operational Improvements through Data Analysis including optimizing marketing strategies for client success at TACT FIRM, identifying peak transit patterns for Metro Medellin, reducing lost calls by 20% at Teleperformance, and increasing actionable insights delivery by 50% at HOME33
About Data Analyst
Possessing over three years of experience in data analysis, this individual demonstrates proficiency in SQL, Excel, and Python. Expertise spans designing and optimizing databases, developing complex queries, building dynamic dashboards, and creating ETL pipelines, all while maintaining rigorous data integrity.
75642
Skills
SQL
Designed and optimized functions, table creations, stored procedures, and views to generate specific reports tailored to client needs, improving efficiency and accuracy in data visualization. Developed and maintained SQL queries to extract and analyze call center metrics, uncovering key performance patterns. Built a robust data pipeline using Python, SQL (PostgreSQL) to aggregate and process real estate data from multiple sources, ensuring data integrity and usability for analytics.
Excel
Built dynamic dashboards with pivot tables and VBA macros for real-time call center KPI tracking. Automated repetitive tasks (e.g., data cleaning, reporting), using VBA Macros and dynamic buttons. Streamlined data migration and quality checks to ensure 100% accuracy in data
Python
Engineered ETL pipelines for real estate data aggregation and processing. Automated data migration between CRM systems (MS Dynamics 365 ↔ Salesforce), reducing manual work. Developed scripts for call center task automation. Conducted reproducible analysis in Jupyter Notebooks for cross-functional collaboration. Cleaned and preprocessed public Metro datasets using Pandas, ensuring data quality and consistency
for accurate analysis and model performance
Power BI
Designed interactive dashboards to visualize real estate market trends, accelerating client decision-making. Integrated SQL queries with Power BI for live reporting, enhancing stakeholder communication. Collaborated with cross-functional teams to design user-friendly interfaces
Looker Studio
Developed a comprehensive dashboard in Looker Studio by integrating BigQuery and Google Cloud Shell, visualizing key performance metrics of Metro lines, and enabling insights into passenger flow patterns. Automated data pulls from SQL databases to ensure up-to-date insights.
Tableau
Transformed raw real estate data into intuitive visualizations. Collaborated with international clients to tailor dashboards for market-specific trends and forecasts