Worked on project focused on optimizing HVAC systems by collecting energy demand data from diverse sources like smart meters, IoT sensors in HVAC systems, weather data, and utility provider API's. Utilized Azure services including Azure Databricks, Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse Analytics, and Power BI for comprehensive data handling - from integration and transformation to storage, analysis, and visualization. Some key responsibilities include building data pipelines for ingesting, and storing data in Azure Data Lake Storage Gen2 while maintaining data quality and ensuring continuous monitoring. Additionally, Databricks is used for data transformation tasks using Spark, enabling our Data Science and Analytics team to develop predictive models for energy demand forecasting and enhance the efficiency and sustainability of HVAC systems through data-driven insights and optimizations.

I worked in the Last Mile Analytics and Quality team to optimize Amazon's delivery process by leveraging real-time geo-spatial data streams collected from mobile applications used by Amazon drivers. The system efficiently extracts, transforms, and loads data for real-time query capabilities. By analyzing this data, insights are derived to pinpoint inefficiencies and bottlenecks in the delivery process, facilitating informed decision-making. Through advanced data processing and analysis techniques utilizing AWS services, the project enabled data-driven decision-making, leading to enhanced delivery route planning, improved navigation accuracy, and overall operational efficiency within Amazon's logistics ecosystem.

I provided actionable, data-driven insights that led to a 45% improvement in customer satisfaction by designing targeted training programs based on performance analysis. I utilized both qualitative and quantitative evaluations of customer associate interactions to generate monthly performance reviews, identifying individual and team strengths and areas for improvement. Additionally, I analyzed historical attendance data to uncover trends in absenteeism, punctuality, and peak attendance times. Leveraging HubSpot, I developed comprehensive reports and interactive dashboards highlighting key metrics such as Average Handle Time (AHT), First Call Resolution (FCR), and Customer Satisfaction Score (CSAT). These visualizations empowered HR teams to track employee engagement and make data-informed management decisions.