As a highly skilled Data Analyst with over six years of extensive experience, I specialize in designing, developing, and managing scalable data pipelines and ETL processes. My expertise in leveraging big data technologies such as Apache Kafka, Spark, NiFi, and Flink, combined with my proficiency in cloud platforms like AWS, Azure, and Google Cloud, empowers me to transform large datasets into valuable insights that fuel strategic decision-making.Adept in utilizing Python and SQL for data manipulation and analysis, I also excel in creating compelling visualizations with tools such as Tableau and Power BI. My commitment to optimizing data workflows and ensuring data integrity, along with my ability to effectively collaborate with cross-functional teams, consistently results in high-quality data solutions that drive business success.Key Achievements; •Data Accuracy Enhancement at Comcast: Utilized Python libraries such as Pandas and NumPy to perform advanced data analysis, resulting in a significant increase in data accuracy. •ETL Optimization: Optimized ETL workflows, decreasing data processing errors and enhancing overall data quality. •Real-Time Data Streaming: Utilized Kafka Connect to create real-time data streaming processes, reducing data latency and improving data availability. •Improved Code Quality: Led initiatives to improve code quality on GitHub, identifying and resolving 30% more issues compared to the previous quarter. •Customer Retention Analysis: Developed complex SQL scripts to analyze customer data, leading to an increase in customer retention rate. •Comcast Customer Data Warehouse Optimization: Implemented ETL processes using Apache Spark and Hadoop, improving query performance by 40% and ensuring accuracy and consistency across multiple data sources. •Predictive Maintenance System at AWS: Developed a predictive maintenance model using Amazon Sage Maker and Python to analyze historical performance data and predict potential failures in network infrastructure.
