This role on the Enterprise Data team is to support Data Engineering initiatives, including the development of “Data Lake” architecture. This role is primarily project based, but also may provide support and maintenance to applications in production.

Responsibilities

• Perform Data Designer activities to transform raw data to meaningful datasets and extracts, such as business logic design, source-to-target mappings, data sourcing strategy, and transformation rules
• Apply strong Data Governance principles, standards, and frameworks to promote data consistency and quality while effectively managing and protecting the integrity of corporate data
• Contribute to the maturation of Data Engineering practices, which may include providing training and mentoring to others

• Minimum 5 years of prior experience as Data Engineer
• Experience in building distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time
• Should have experience in creating metrics and apply business logic using Python, Spark, Scala and/or R
• Programming experience with the Hadoop ecosystem of applications and functional understanding of distributed data processing systems architecture (Data Lake / Big Data /Hadoop/ Spark / HIVE, etc)
• Experience in developing, deploying and operating on large scale distributed systems on a commercial scale
• Experience working in Cloud-based Big Data Infrastructure. Azure Big Data ecosystem experience is preferred
• Proficiency in Python 3.5 or later
• Good SQL knowledge, ability to analyze data and create complex SQL queries
• Good knowledge of Netezza, Informatica Enterprise Data Catalog and DataStage is a huge plus
• Good working experience on Cloud, Delta Lake, ETL processing
• Knowledge of Insurance domain is a plus