Join EY's GDS Consulting team as a Senior AI Data Platform Engineer specializing in AWS. This role offers the opportunity to build and manage cutting-edge AWS-native Data & AI platforms, driving innovation in data engineering and platform operations. You will be instrumental in developing production-grade solutions for complex data and AI workloads, contributing to EY's mission of building a better working world.

This position is within EY's Consulting Services, focusing on the Data and Analytics team. You'll leverage deep industry experience and technical capabilities to solve significant business challenges, embedding advanced analytical practices into client decision-making processes. We are looking for individuals passionate about technology and its potential to transform businesses.

Key responsibilities include designing and building robust AWS data pipelines utilizing services like S3, Glue, PySpark, Athena, Redshift, EMR, and MWAA. You will develop reusable ingestion frameworks for various data patterns and construct curated data layers using scalable lakehouse architectures. Performance and cost optimization of Spark/Glue/EMR workloads are critical.

Platform engineering involves creating accelerators for onboarding, orchestration, monitoring, and deployment. You will implement Git-based workflows, CI/CD, and Infrastructure as Code. Integration with enterprise APIs, source applications, and governance tools is essential.

Furthermore, you will integrate data platforms with Amazon SageMaker for data preparation, model training, and MLOps. Applying AI-assisted operations for anomaly detection, diagnostics, and data quality enhancements is also a key aspect of this role. Implementing comprehensive data security controls and owning Data SRE responsibilities, including observability, incident response, and production reliability, are vital.

We are seeking experienced professionals with 5-10 years in data engineering, data platform operations, analytics engineering, or AI platform enablement. A strong track record in cloud data platforms, API integration, Git workflows, CI/CD, governed access patterns, SRE practices, and production operations is mandatory.

Ideal candidates possess a strong engineering background with architectural awareness and a delivery-focused mindset. You should be adept at translating platform standards into reusable frameworks and operational controls. The ability to mentor junior engineers, collaborate effectively with cross-functional teams (architecture, security, SRE), and embrace new AI-native engineering methods is highly valued. Preferred certifications in relevant cloud/platform stacks, data engineering, DevOps, security, governance, and AI/ML are a plus.