As a Data Engineer, you will be responsible for creating, scheduling, and optimizing data processing pipelines using Apache Spark and Apache Airflow. This involves building reusable components, cleaning and processing data for analysis, and implementing internal process improvements to enhance data delivery and infrastructure scalability.
The ideal candidate must have a minimum of 7 years of hands-on experience in building complex data pipelines. Strong technical skills are required, including expertise in Apache Spark, Python, SQL, data manipulation, transformation techniques, and experience with deployment automation tools like Docker and Kubernetes.
EY offers a dynamic work environment with opportunities for continuous learning, professional growth, and meaningful impact. The role provides competitive compensation, flexible work arrangements (2 days in-office, 3 days remote), and the chance to work with global teams across various service lines and sectors.
