Professional Summary:•Experienced programmer with 3+ years in Big Data technologies, adept at end-to-end data project implementation. Skilled in ETL processes, encompassing data ingestion, pipeline design, and modeling.Technical Skills:•Big Data Technologies: Hadoop, Hive, Parquet, HDFS, MapReduce, Sqoop, Oozie, Unix•Querying Tools: Hive, Impala•Cloud Platforms: Azure (Data Bricks, Data Lake, Data Factory, Pipeline)•ETL Tools: Data bricks, Hue•Programming Languages: Spark SQL, Shell Script, SQL, Python, Hive, Impala•Databases: Oracle, SQL, PostgreSQL, Data bricks SQL (DB SQL), DBeaver•Tools & Utilities: Jira, Jenkins, Git, CONTROL-M•Execution Methodology: Agile•Versioning Systems: Bit Bucket•Operating Systems: Windows (98/XP/7/8/10), LinuxRole/Responsibilities:•Extensive experience in Big Data technologies: Hive, Impala, Oozie, Hadoop, MapReduce.•Development and maintenance of Spark SQL applications on Cloudera.•Utilized Spark SQL APIs for performance comparison with Hive and SQL.•Hands-on involvement in ETL processes: data ingestion, pipeline design, modeling, and advanced processing.•Creation of test plans and scripts for testers and business analysts.•Utilization of Spark-SQL for structured data handling and loading into Hive tables. Implemented Impala for optimized querying of HDFS data.•Importation of data from HDFS into Spark RDDs, performing transformations.•Integrated Sqoop for data import from SAP, MySQL, and Teradata Systems into HDFS.•Creation and optimization of Hive queries, managing tables, and partitioning for cost-saving.•Development of Oozie Workflow for automating data loading and transformations.•Automation of jobs in Jenkins using shell scripts.•Optimized HQL queries and scheduled Hive/Impala/Spark jobs through Coordinator/Control-M.