Key Responsibilities Data Analysis • Extract, clean, and analyze large datasets from both vendor systems to identify trends, patterns, and actionable insights. • Apply advanced statistical methods and data mining techniques to interpret data and generate meaningful business insights. Reporting and Visualization • Design, develop, and maintain interactive dashboards and reports using industry-leading BI tools such as Power BI and Tableau. • Present findings in a clear, concise, and visually appealing manner, tailored to both technical and non-technical audiences, enabling informed decision-making across the organization. Requirements Gathering: • Collaborate with business stakeholders to understand and document reporting requirements, data needs, and key performance indicators (KPIs). • Translate business questions into structured analytical projects and develop comprehensive requirements documentation that guides data-driven initiatives. Data Modeling • Assist in the design, implementation, and optimization of data models that support the organization's reporting and analytical needs. • Ensure the accuracy, consistency, and integrity of data throughout the entire reporting process, from extraction to final visualization. Continuous Improvement • Stay current with industry trends, emerging technologies, and best practices in BI and analytics to drive innovation within the team. • Proactively propose and implement enhancements to existing reporting processes, aiming to increase efficiency, accuracy, and overall business value. What We are Looking For: • Bachelor's degree in business, Computer Science, Statistics, or related field. • Proven experience as a BI Analyst or in a similar analytical role. • Proficiency in SQL for data extraction and manipulation. • Experience with BI tools such as Power BI, Tableau, or similar. • Strong analytical and problem-solving skills. • Excellent communication and presentation abilities. Preferred Skills • Knowledge of data warehousing concepts and ETL processes. • Programming skills in languages such as Python or R. • Familiarity with database systems (e.g., Microsoft SQL Server, Oracle).