With an extensive 15-year tenure in Development, I've specialized in Data Engineering and Datawarehouse projects across diverse sectors, including Retail, Payment, and Banking.My technical expertise is broad and deep, encompassing Python, Micro Service Framework, PySpark, Java, Spark Scala, Apache Airflow, Selenium, and the Hadoop Ecosystem (Pig, Hive, Impala, Spark, Kafka HBase). I'm proficient in Google Cloud Platform, Informatica, Mongo, and various databases - Oracle, PostgreSQL, MySQL, SQL Server IBM DB2, to name a few. I also possess proficiency in Groovy, Apache Airflow, and Unix shell scripting. My performance tuning skills in Oracle SQL and PL/SQL are well-honed, leveraging hints, partitioning, join types, and various indexes.I have a solid understanding of design and architecture in data pipeline creation, utilizing Google Cloud Services for both streaming and batch data engineering projects. I've successfully designed and developed decoupled Microservice App engine frameworks using Python flask, demonstrating extensive knowledge and effective utilization of GCP ecosystems.My expertise extends to Kafka Architecture, encompassing Producer, Broker, Consumer, Kafka Source Connect, and Stream API. I have hands-on experience developing Kafka Producer and Consumer framework code in Java and creating Partition, Topic, and Replication.Throughout my career, I've collaborated with leading organizations in the Payment domain, enriching my knowledge by working with technical experts, understanding business requirements, and providing effective solutions.I've gained hands-on experience on numerous migration projects, converting complex legacy ETL processes and handling large volumes of data in both relational and non-relational databases. This includes identifying bottlenecks, performance fine-tuning long-running processes, and implementing error handling techniques in Oracle and Python.