Sr. Hadoop Developer
Current• Created end to end spark applications for performing various data transformation activities.• Created series of ingestion jobs using Sqoop, Kafka, custom Input adapter etc. to move data from multiple sources to HDFS.• Developed simple to complex Map Reduce jobs using Java language for processing and validating the data. • Developed data pipeline using Sqoop, Spark, Map Reduce, and Hive to ingest, transform and analyze customer behavioral data.• Developed Spark jobs to discover trends in data usage by users.• Implemented Spark using Scala and utilizing Dataframes and Spark SQL API for faster processing of data.• Used Spark for interactive queries, processing of streaming data and integration with popular NoSQL database for huge volume of data.• Real time streaming the data using Spark with Kafka• Handled importing data from different data sources into HDFS using Sqoop and also performing transformations using Hive.• Exported the analyzed data to the relational databases using Sqoop to further visualize and generate reports for the BI team.• Collecting and aggregating large amounts of log data using Flume and staging data in HDFS for further analysis• Analyzed the data by performing Hive queries (Hive QL) and running Pig scripts (Pig Latin) to study customer behavior.• Used Hive to analyze the partitioned and bucketed data and compute various metrics for reporting.• Developed Hive scripts in Hive QL to de-normalize and aggregate the data.• Created HBase tables and column families to store the user event data.• Written automated HBase test cases for data quality checks using HBase command line tools.• Scheduled and executed workflows in Oozie to run Hive and Spark jobs.• Configured Kafka to read and write messages from external programs.• Continuous monitoring and managing the Hadoop cluster using Cloudera Manager.• Developed interactive shell scripts for scheduling various data cleansing and data loading process.