⤷ Develop scalable data pipelines, leveraging Fabric's Lakehouse architecture.⤷ Develop Power Apps & Power Automate Approval Flows.⤷ Apply advanced analytical techniques: machine learning models or statistical analysis using PySpark.⤷ Design data models in Fabric’s Warehouse, ensuring accurate schema representation and efficient querying.⤷ Automate ETL processes to move, cleanse, and structure data from multiple sources into Fabric's Lakehouse using Data Pipelines, Dataflows, and PySpark Notebooks.⤷ Monitor the performance of data pipelines, data models, and PowerBI reports to improve processing times.⤷ Design and develop PowerBI dashboards

● Developed a robust SQL Data Warehouse, integrating SQL Server, ERP, CRM, JSON data sources, facilitating streamlined data access.● Automated critical processes across Personnel, Payroll, Recruitment, and OD divisions, enhancing operational efficiency.● Established a reporting infrastructure using PowerBI for the company's owners, providing intuitive insights for informed decision-making.➤ Python, MSQL Server, Tableau, Excel, Google Sheets, and PowerBI in the process.

● Built out the scouting department's SQL database through Web scraping data from popular sports websites such as: Whoscored, Transfermarkt, Sofascore, and FbREF.● Built out the club's reporting infrastructure utilizing Python, Tableau, and SQL to provide insights into the performance analysis department.➤ Utilized Tableau and Python to create different types of plots for the scouting and opposition analysis departments.

Assisted superiors in the data modeling, mining, and production phases using Excel, Python, and PowerBI.