Srinivasulu Banda Email & Phone Number

Richmond, Virginia, United States

Worked extensively with AWS S3 for scalable and secure data storage, managing data lakes, and optimizing data retrieval performance. Implemented AWS DynamoDB to develop high-performance NoSQL database solutions and crafted ETL workflows using AWS Glue to accurately extract, transform, and load data into AWS Redshift and PostgreSQL. Integrated streaming data sources with AWS Kinesis for high-velocity ingestion into EMR and enforced secure user access management with IAM.Automated ETL processes and data transformations with Python, enhancing efficiency and reducing manual effort. Developed complex data processing solutions using PySpark, and leveraged Databricks for Apache Spark-based processing, including data transformations, machine learning, and real-time analytics. Designed and optimized distributed data processing pipelines with Spark and PySpark, and fine-tuned Spark jobs and real-time streaming applications for optimal performance.Worked with Hadoop ecosystem technologies (HDFS, MapReduce, Hive, Sqoop), optimizing workflows through Databricks. Managed NoSQL databases like MongoDB and Cassandra, performed maintenance and performance tuning for MySQL and PostgreSQL databases, and developed data integration processes to ensure consistency across systems. Utilized Snowflake’s time travel features with Databricks for historical data analysis, and created secure visualizations and dashboards in Tableau. Employed Git for version control and JIRA for project management, applying Agile and Scrum methodologies to improve team collaboration.

Hyderabad, Telangana, India

Implemented and managed ETL processes using Informatica to ensure seamless data integration, transformation, and orchestration across multiple sources. Administered and optimized Azure SQL databases for high availability, security, and performance, and leveraged Azure Data Lake for large-scale data storage and advanced analytics. Developed and maintained data warehousing solutions with Azure Synapse Analytics, creating robust ETL workflows to ensure data accuracy and reliability.Automated ETL processes with Informatica and Apache NiFi, reducing manual intervention and enhancing efficiency. Utilized Spark SQL and Python for advanced data transformations, and created data pipelines using Spark and Hive. Developed real-time data models with Spark Streaming, and wrote efficient Spark code using Spark SQL and Scala. Troubleshot and optimized CI/CD pipelines with Docker and Jenkins for Hadoop jobs.Designed and implemented SQL and NoSQL database schemas, including MongoDB, MySQL, and PostgreSQL, for optimized data storage and retrieval. Configured Snowflake data warehouses for scalable performance and developed interactive dashboards with Power BI to provide actionable insights. Managed version control with Git and GitHub, and used JIRA for Agile project management, ensuring code integrity and alignment with project goals.

Gurgaon, India

Integrated AWS Kinesis for real-time streaming and automated deployments using Python scripts, optimizing data workflows with AWS services like S3, Step Functions, and Lambda. Built robust data pipelines with AWS Glue, storing weblog data in HDFS, and processed it with Apache Spark and Presto on Amazon EMR and Redshift.Designed ETL tools to extract and load data from various databases such as DB2, Oracle, and XML. Implemented Spark with Python to accelerate data processing, transforming Hive/SQL queries into Spark operations for enhanced performance. Configured Snowflake for efficient data storage and processing and created interactive Tableau dashboards for actionable insights.Developed AWS pipelines for seamless data extraction from diverse sources including Excel, Oracle, Flat Files, SQL Server, and Teradata into Hadoop HDFS. Managed version control with Git and utilized JIRA for project tracking and management. Optimized complex SQL queries and ensured data integrity through meticulous validation with SQL scripts.