Generating a Big Data solution using Spark and Scala to analyze the MovieLens dataset (1 million records), answering analytical questions on movie ratings, genres, and user behavior.Leveraging Spark RDD, Spark SQL, and Spark DataFrame to process and analyze large datasets, improving data processing speed; utilizing Cassandra for efficient data storage.Exposing the solution as an API, implementing logging for tracking over 100+ actions, and managing code on GitHub, ensuring modularity and following best practices.Deploying the solution on cloud platforms such as AWS or GCP, optimizing performance and latency using Ops Pipeline tools like Jenkins and Azure DevOps.

During my equity options trading journey, I conducted thorough market analysis to identify trading opportunities and developed effective strategies such as spreads and hedges. I diligently managed risk by monitoring positions and using stop-loss orders to protect my capital, ensuring timely trade execution across various platforms. By maintaining a trading journal, I tracked my performance and refined my strategies, while continuously learning about market trends and regulations to enhance my skills. My efforts resulted in consistent profitability, effective risk mitigation during downturns, and successful capitalization on key market trends.

At TEKsystems Global Services, I enhanced data operations for two major projects, streamlining data workflows using PySpark and AWS Glue, reducing processing time by 30%. I also integrated data into Databricks and Athena, boosting report distribution efficiency by 40%, improving decision-making and data accuracy.