Shape your future in a dynamic global environment with EY. We are seeking a highly skilled Senior AWS Data Engineer to design, develop, and maintain modern cloud-based data platforms on Amazon Web Services (AWS). This role is crucial for building and managing scalable data ingestion, transformation, and analytics pipelines that support critical financial services applications. Prior experience in Wealth & Asset Management (WAM) domains is a significant advantage.

Join our Global Delivery Services team, a worldwide network of service delivery centers that plays a vital role in EY's growth strategy. With over 80,000 professionals across ten global locations, we provide cost-effective, high-skilled, and innovative services. This opportunity allows you to leverage cutting-edge technologies and contribute to building a better working world.

As a Senior AWS Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines utilizing AWS Glue (PySpark), Amazon S3, AWS Step Functions, and Athena. You will build robust ETL/ELT solutions for batch and near real-time data processing, and develop reusable PySpark frameworks. Responsibilities also include implementing and supporting enterprise data lakes using Medallion Architecture, developing Apache Iceberg tables, and ensuring data quality, lineage, and auditability.

You will develop and maintain Apache Airflow (MWAA) workflows, automating data movement, monitoring, and notification processes. Implementing AWS security best practices, supporting infrastructure provisioning with Terraform, and collaborating with DevOps and security teams are key aspects of this role. Furthermore, you will monitor and troubleshoot production data pipelines, perform performance tuning, and participate in incident resolution and continuous improvement initiatives.

This role requires a Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline, along with 5-8 years of dedicated data engineering experience with significant AWS exposure. Essential hands-on experience includes AWS Glue, Amazon S3, Athena, MWAA (Apache Airflow), Step Functions, and CloudWatch. Strong programming proficiency in Python and PySpark is mandatory, alongside experience in building large-scale ETL/ELT data pipelines and a solid understanding of data modeling, warehousing, and distributed processing concepts.

Candidates must have experience with Apache Iceberg, cloud-native data lake architectures, and Infrastructure as Code tools like Terraform. Excellent SQL development and query optimization skills are expected, as is experience supporting production-grade data platforms and troubleshooting complex issues. A good understanding of AI technologies, agentic systems, and tools such as Microsoft Copilot and Claude is also a requirement for leveraging AI-driven capabilities in solution development.