• Assist in designing and structuring database architecture to support scalable data storage, efficient querying, and optimized performance. • Demonstrate understanding of relational databases, including tables, schemas, indexing, normalization, and relationships. • Help build and maintain data pipelines to move and transform data between systems while ensuring accuracy and reliability. • Create dashboards, reports, and visualizations using SQL, Excel, Tableau, Power BI, or Looker Studio to communicate findings clearly to stakeholders. • Analyze large datasets to identify trends, patterns, correlations, and actionable insights that support business decisions. • Collect, organize, and maintain data from multiple sources while ensuring data integrity and accuracy. • Write, maintain, and optimize SQL queries for reporting, analysis, and data extraction. • Clean, preprocess, and transform raw data using SQL and Python to prepare it for analysis and reporting. • Work with cross-functional teams to understand business requirements, define KPIs, and translate them into analytical solutions. • Identify inefficiencies in data processes and implement automation using SQL, Python, or ETL tools to improve workflow and data quality.