Roles & Responsibilities
• Create Scala/Spark/Pyspark jobs for data transformation and aggregation
• Produce unit tests for Spark transformations and helper methods
• Used Spark and Spark-SQL to read the parquet data and create the tables in hive using the Scala API
• Work closely with Business Analysts team to review the test results and obtain sign offPrepare necessary design/operations documentation for future usage
• Perform peers Code quality review and be gatekeeper for quality checks
• Hands-on coding, usually in a pair programming environment
• Working in highly collaborative teams and building quality code
• The candidate must exhibit a good understanding of data structures, data manipulation, distributed processing, application development, and automation
• Familiar with Oracle, Spark streaming, Kafka, ML
• To develop an application by using Hadoop tech stack and delivered effectively, efficiently, on-time, in-specification and in a cost-effective manner
• Ensure smooth production deployments as per plan and post-production deployment verification
• This Hadoop Developer will play a hands-on role to develop quality applications within the desired timeframes and resolving team queries
Requirements
• Hadoop data engineer with total 4 - 7 years of experience and should have strong experience in Hadoop, Spark, Scala, Java, Hive, Impala, CI/CD, Git, Jenkins, Agile Methodologies, DevOps, Cloudera Distribution
• Strong Knowledge in data warehousing Methodology
• Relevant 4+ years of Hadoop & Spark/Pyspark experience is mandatory
• Strong in enterprise data architectures and data models
• Good experience in Core Banking, Finance domain
• Good to have Cloud experience on AWS