Manoj Kudikala Email & Phone Number

Chicago, Il, Us

Virginia, United States

• Implemented Agile methodologies, improving project flexibility and accelerating development cycles by 20%, reducing time-to-market for data-driven initiatives.• Lead the design and deployment of data processing pipelines using Python, R, SQL within the Hadoop ecosystem (Hive, Pig, MapReduce), increasing processing efficiency by 40%.• Optimized big data applications with Apache Spark, cutting batch data processing times and resource consumption, streamlining operations.• Architected ETL processes with SSIS and AWS Glue, ensuring seamless data flows between SQL databases and cloud platforms (AWS, Azure) for high data consistency.• Developed real-time data streaming solutions with Apache Kafka and Scala, improving data feed reliability by 40%.• Configured and optimized Amazon EC2 instances for scalability and cost-efficiency, aligning server capacity with workload demands.• Leveraged Amazon Athena to run SQL queries on S3 data, reducing query response times by 20% and streamlining data analysis.• Created interactive dashboards with Power BI, SSRS, and Tableau, improving data driven decision-making by 25%.

India

• Designed and implemented cloud-based data pipelines using Azure Data Factory and AWS Kinesis, enhancing data integration across distributed systems and improving model scalability.• Integrated Hadoop, Spark, and Hive with SQL databases, optimizing large-scale data warehousing processes and reducing financial data retrieval times by 50%.• Spearheaded the adoption of Snowflake and BigQuery for advanced data warehousing, decreasing query execution times by 45%.• Crafted Python scripts for data ingestion and transformation, optimizing the management of complex financial datasets, increasing data accuracy by 30% through efficient MapReduce jobs.• Engineered real-time data monitoring systems using Apache Kafka, enabling immediate financial analysis and rapid market response, reducing error rate by 25%.• Applied machine learning models (TensorFlow, Scikit-learn) to forecast market trends with 20% higher accuracy, contributing to improved risk management and decision-making.• Managed containerized deployments with Docker and Kubernetes, improving application scalability and operational efficiency in cloud environments.• Created tailored financial dashboards with QuickSight and Matplotlib, enhancing strategic planning and improving decision-making efficiency by 40%.