Ravi Teja Reddy P Email & Phone Number

• Designed and implemented end-to-end data pipelines using Azure Data Factory to facilitate efficient data ingestion, transformation, and loading (ETL) from diverse data sources into Snowflake data warehouse.• Orchestrated robust data processing workflows utilizing Databricks and Apache Spark for seamless large-scale data transformations and advanced analytics improving data processing speed by 14%.• Developed real-time data streaming capabilities into Snowflake by seamlessly integrating Azure Event Hubs and Azure Functions, enabling prompt and reliable data ingestion.• Deployed Azure Data Lake Storage as a reliable and scalable data lake solution, implementing efficient data partitioning and retention strategies to store and manage both raw and processed data effectively.• Employed Azure Data lake Storage Gen 2 for optimized data file storage and retrieval, implementing advanced techniques like compression and encryption to bolster data security and streamline storage costs.• Integrated Azure Logic Apps seamlessly into the data workflows, ensuring comprehensive orchestration and triggering of complex data operations based on specific events, enhancing overall data pipeline efficiency.

Dallas, Texas, United States

• Creating pipelines, data flows and complex data transformations and manipulations using ADF and PySpark with Databricks.• Data Ingestion to one or more cloud Azure Services - (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and cloud migration processing the data in Azure Databricks.• Used Data Flow debug for effectively building ADF data flow pipelines. Improved performance by using optimization options by effectively using partitions during various transformations.• Created complex ETL Azure Data Factory pipelines using mapping data flows with multiple Input/output transformations• Worked on Azure BLOB and Data Lake storage and loading data into Azure SQL Synapse analytics (DW).• Worked with Azure SQL Database Import and Export Service.• Used Azure Key vault as central repository for maintaining secrets and referenced the secrets in Azure Data Factory and also in Databricks notebooks.• Built a common SFTP download or upload framework using Azure Data Factory and Databricks.• Developed Databricks ETL pipelines using notebooks, Spark Data frames, SPARK SQL and python scripting.• Created Databricks Job workflows which extracts data from SQL server and upload the files to SFTP using PySpark and python.

Texas, United States

• Imported Data using Sqoop to load Data from MySQL to HDFS on regular basis.• Worked with Data Lakes and big data ecosystems (Hadoop, Spark, Hortonworks, Cloudera).• Load and transform large sets of structured, semi structured, and unstructured data.• Written Hive queries for data analysis to meet the Business requirements.• Built HBASE tables by leveraging on HBASE Integration with HIVE on the Analytics Zone.• Hands on experience in using Kafka, Spark streaming, to process the streaming data in specific use cases.• Developed data pipeline using Flume, Sqoop to ingest customer behavioral data histories into HDFS for analysis.• Worked on analyzing Hadoop cluster using different big data analytic tools including Hive, and MapReduce.• Developed a data pipeline using Kafka, Spark, and Hive to ingest, transform and analyzing data.• Wrote Hive queries for data analysis to meet the specified business requirements by creating Hive tables and working on them using Hive QL to simulate MapReduce functionalities.• Written Hive queries for data analysis to meet the Business requirements.

Boyertown, Pennsylvania, United States

• Designed and developed data warehouse architectures, including dimensional models and ETL processes, to support reporting and analytics needs.• Implemented ETL processes to extract, transform, and load data from various sources (databases, APIs, flat files, streaming platforms) into the data warehouse.• Identified and resolved performance bottlenecks through query optimization, indexing strategies, and database configuration adjustments, resulting in improved query response times and overall system performance.• Utilized session logs and workflow logs for effective error handling and troubleshooting in development environments, ensuring ETL process stability and integrity.• Successfully deployed SSIS packages and configured jobs to ensure efficient execution and optimal performance.• Orchestrated SSIS package deployment and automated execution through job scheduling, enhancing the efficiency and reliability of data integration processes.

St Louis, Missouri, United States

• Excellent Experience in monitoring SQL Server Performance tuning in SQL Server• Expert in designing ETL data flows using SSIS, creating mappings/workflows to extract data from SQL Server and Data Migration and Transformation from Access/Excel Sheets using SQL Server SSIS.• Efficient in Dimensional Data Modeling for Data Mart design, identifying Facts and Dimensions, and developing, fact tables, dimension tables, using Slowly Changing Dimensions (SCD).• Experience in Error and Event Handling: Precedence Constraints, Break Points, Check Points, Logging.• Experienced in Building Cubes and Dimensions with different Architectures and Data Sources for Business Intelligence and writing MDX Scripting.• Thorough knowledge of Features, Structure, Attributes, Hierarchies, Star and Snow Flake Schemas of Data Marts.• Experience in creating Ad hoc reports and reports with complex formulas and to query the database for Business Intelligence.