Overview
About Business Unit:
The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team of innovative problem solvers develops and builds products that position Epsilon as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full-cycle product engineering and data teams chart the future and set new benchmarks for our products, by using industry standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence. Driven by a passion for delivering smart end-to-end solutions, this team plays a key role in Epsilon's success story.
The Data Engineering team at Epsilon plays a pivotal role in building the next-generation data platforms that empower Epsilon's ecosystem. We design, develop, and optimize scalable, high-performance data solutions that process terabytes of data every day, driving intelligent insights for clients across industries.
This team of problem-solvers and innovators uses up-to-date big data, cloud, and automation technologies to deliver reliable and efficient data products.
Candidate will be a member of the Data Engineering Team and be responsible for developing, Unit Testing, and implementing applications for the Data engineering group predominantly in the Hadoop Ecosystem and Databricks.
Why we are looking for you:
- You have good knowledge of Databricks implementations and are ready to leverage this expertise to migrate and modernize Hadoop ecosystem workloads on Databricks..
- You are hands-on with big data technologies like Spark, PySpark, Hive, and Hadoop, and enjoy working with massive datasets.
- You have experience working with AWS.
- You have strong experience in building and optimizing large-scale data engineering pipelines.
- You are self-driven, thrive in solving complex problems, and can mentor and guide junior