- 5+ years of experience in building data-intensive applications, tackling challenging architectural and scalability problems. - Responsible for data engineering functions including, but not limited to: - data extract, transformation, loading, integration in support of enterprise data infrastructures – data warehouse, operational data stores and master data management. - Hands-on experience in Big data and Hadoop framework – HIVE, IMPALA, SQOOP, HDFS and SPARK. - Good exposure and working knowledge in cloud platform AWS – Redshift, Aurora DB, Glue, Dynamo DB including EC2 and RDS instances. - Proficient working experience in creating and handling complex SQL queries, Stored Procedures, and functions. - Working knowledge in developing statistical and machine learning techniques to build models that address business needs. - Understand correlation, multivariate regression and all aspects of massaging data to look at it from different angles for use in predictive and prescriptive modeling - Working experience in multiple programming languages like Python, PySpark, and Java. - Capable of processing and handling large sets of structured, unstructured, and semi-structured data. - Designing ETL and data pipelines as per the requirements. - Experience in developing PySpark ETL job scripts in AWS Glue for data transformation and processing. - Extensive knowledge in ETL/ELT concepts and hands on experience in using ETL tools like Talend Open Studio – DI and Big Data tools.