T Praneeth Email & Phone Number

Atlanta, Georgia, United States

• Designed and implemented data pipelines using Google Cloud Dataflow, ensuring efficient data extraction, transformation, and loading (ETL) from multiple sources.
• Developed Spark Streaming applications for real-time data processing, seamlessly integrating data from Kafka into Azure Data Lake Storage.
• Implemented data transformation logic using PySpark within Google Cloud Dataproc, optimizing workflows for performance and resource utilization.
• Built end-to-end ETL workflows with Apache Airflow for orchestrating data ingestion into Azure SQL Database, ensuring data integrity and reliability.
• Conducted performance tuning and optimization of Spark jobs in both GCP and Azure environments, reducing processing times and improving resource utilization.
• Developed real-time analytics solutions using Google Cloud Pub/Sub, enabling actionable insights from streaming data.

• Developed and optimized Spark applications using PySpark and Spark-SQL for data extraction, transformation, and aggregation from diverse file formats, enhancing analytical capabilities.
• Designed and implemented efficient data pipelines using Google Cloud Dataflow, Cloud Functions, and Google Cloud Storage (GCS) to facilitate robust data handling.
• Developed Spark Streaming applications to consume and process real-time data from Kafka, ensuring data integrity by inserting processed streams into Google Cloud Bigtable.
• Ensured high code quality through rigorous code reviews, unit testing, and debugging of Python applications, enhancing reliability and maintainability.
• Leveraged Google BigQuery for ad-hoc querying and analysis of large datasets stored in GCS, optimizing query performance and resource efficiency.
• Supported and optimized critical deployments on Google Cloud Functions, focusing on CI/CD pipelines to enhance DevOps practices.

Atlanta, Georgia, United States

• Spearheaded the development of scalable distributed data solutions utilizing Azure Data Lake, Azure Databricks, Azure HDInsight, and Azure Cosmos DB, meeting stringent scalability and performance requirements for large.
• Managed the migration of on-premises SQL databases to Azure services, including Azure Data Lake, Azure SQL Database, and Azure Data Warehouse, ensuring secure database access and permissions throughout the process.
• Developed automation scripts in PySpark and UNIX shell to enhance efficiency, including DAG name retrieval and data validation processes, streamlining workflows.
• Designed and implemented end-to-end data pipelines for data visualization and analytics, ensuring seamless data synchronization across multi-data center environments.
• Created the conceptual model for the data warehouse using Erwin Data Modeling tool, enabling a structured approach to data architecture.
• Developed Scala-based applications and services for data processing, analysis, and visualization, facilitating data-driven decision-making.

Pine Bluff, Arkansas, United States

- Worked extensively with importing metadata into Hive using Python and migrated existing tables and applications to work on the AWS cloud (S3). - Data Extraction, aggregations, and consolidation of Adobe data within AWS Glue using PySpark.- Involved in the complete Big Data flow of the application starting from data ingestion from upstream to HDFS.

Irving, Texas, United States

- Created ETL/Talend jobs both design and code to process data to target databases. - Experience in testing Big Data Hadoop (HDFS, Hive, Sqoop, and Flume), Master Data Management (MDM), and Tableau Reports. - Experienced in loading the real-time data to NoSQL database like Cassandra. - Performed Data scrubbing and processing with Apache NiFi and for.

Dallas, Texas, United States

- Designed and Developed ETL data pipelines using Scala and Spark.- Automated workflows using the Oozie job scheduling tool.- Experience in testing Big Data Hadoop (HDFS, Hive, Sqoop, and Flume), Master Data Management (MDM), and Tableau Reports.- Experienced in creating the Hive schema, external tables, and managing views.- Experience in layers of Hadoop.

Master'S Degree, Management Information Systems, General

Bachelor'S Degree, Information Technology