5+ Years of Expertise in Hive QL, Python programming, experience with Spark, Python, Scala and Spark for big data processing and analysis.
5+ Years of Strong proficiency in AWS services, including AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions and Lambda.
Fair experience with any Visualization Tools such as Tableau or PowerBI is a plus
2+ years of experience with ETL technologies such as Informatica Powercenter or SSIS coupled with most recent 2-3 years of cloud ETL technologies
2+ years of experience in dealing with data pipelines associated with modern data platforms such as Snowflake or Databricks with Pyspark/ Snowpark
Exposure to Data Virtualization tools such as Starburst or Denodo is a plus
Strong problem-solving skills and the ability to optimize and fine-tune data pipelines and Spark jobs for performance.
Experience working with data lakes, data warehouses, and distributed computing systems.
Experience with Modern Data Stack and Cloud Technologies is a must.
Job Classification
Industry: Financial ServicesFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time