• Design and development, unit testing, integration, deployment packaging and checkout, scheduling, of various components in Informatica Power Center, Azure Data Factory and Azure Data Bricks through several SDLCs for implementing ETL/ELT processes for cloud based very large data warehouse and ODS integrated with data for subject areas from disparate data sources and processes supporting downstream data marts.• Performed analysis of ETL/ELT applications and database systems, data structure analysis, data profiling for application design and defects resolution.• Converted legacy ETL processes into Azure synapse compatible architecture using regular expression driven metadata conversion such as ODBC/ JDBC reads and OLAP writers and replacements such as bulk merges, deletes with OLAP model.• Performed process enhancements such as capacity improvement, tuning/optimization and performance improvement of the Azure Hyperscale based ETL/Upsert processes.• Performed extensive metadata gathering and analysis of database and metadata repositories for understanding data lineage, data flow, process design, process statistics and identifying storage elements and access to data using JSON, XML, AVRO.• Partnered with DBA/SA to optimize database tables/indexes, partitioning, parallelization and in implementing database/client configurations to support pipeline partitioning and multi-threaded processing.

• Design and development, unit testing, integration, deployment packaging and checkout, scheduling, of various components in Informatica Power Center, Azure Data Factory and Azure Data Bricks through several SDLCs for implementing ETL/ELT processes for cloud based very large data warehouse and ODS integrated with data for subject areas from disparate data sources and processes supporting downstream data marts.• Performed analysis of ETL/ELT applications and database systems, data structure analysis, data profiling for application design and defects resolution.• Performed process enhancements such as capacity improvement, tuning/optimization and performance improvement of the Azure Hyperscale based ETL/Upsert processes.• Performed extensive metadata gathering and analysis of database and metadata repositories for understanding data lineage, data flow, process design, process statistics and identifying storage elements and access to data using JSON.• Partnered with DBA/SA to optimize database tables/indexes, partitioning, parallelization and in implementing database/client configurations to support pipeline partitioning and multi-threaded processing.• In the event human intervention is required for correction, build a flexible error correction management workflow with ability for effective workload management while providing visibility on the error corrections.• Streamlined SDLC processes by automating data sampling and data comparison for testing and analysis of source and target data for ETL application development, QA and UAT.• Performance Tuning: Enhanced and troubleshoot ETL process runtime contingencies applying Database tuning, query tuning and application tuning solutions.

• Conceptualized Audit and Control Framework for ETL application system for Enterprise Data Warehouse initiative at SSA on Informatica Power Center platform. Implemented the framework by designing and developing ETL components in Informatica, Oracle and shell scripts.• Troubleshoot with Informatica to rebrand the ODBC drivers by identifying parallel performance and driver error issues.• Involved in managing and monitoring Hadoop clusters using Cloudera Manager.• Used Python and Shell scripting to build pipelines.• Developed data pipeline using Sqoop, HQL, Spark and Kafka to ingest Enterprise message delivery data into HDFS.• Implementing Data Security Policies in the Informatica Dynamic Data Masking server.• Configuring DDM environments planned for enterprise-wide databases classified by data applications.• Developing and configuring DDM services, connection rules, and security rules for clustered DDM server nodes for Partial, Full and No Masking policies and user access classification.• Developing Informatica DDM best practices for data security policy management, maintenance and deployment that requires migration, replication and synchronization of security rules, domains and services.• Troubleshoot QA defects in rule matchers and rule actions for data masking and rewrites for SQL requests containing simple and nested queries. Masking for multi-result sets stored procedure database requests.• Improved performance with best possible optimal combination of Informatica, UNIX Shell Scripts and database SQL or Procedure objects by choosing the better over the lesser.• Improved performance of ETL processes by employing performance bottleneck resolutions to Informatica Mappings, configuring Transformations.