Join EY and build a career that's as unique as you are, leveraging global scale, support, and an inclusive culture. We are seeking an AWS Data Platform Architect/Engineering Manager to lead enterprise-scale AWS Data & AI platforms. This role is instrumental in shaping AWS data platform strategy, driving modernization and migration programs, and establishing robust engineering standards.

EY's Consulting Services focuses on industry-specific solutions, offering integrated services that combine deep industry experience with strong functional, technical capabilities, and product knowledge. Our Data and Analytics team tackles complex issues and identifies opportunities to deliver significant business outcomes, embedding advanced analytical practices at the core of client decision-making.

This position offers the opportunity to architect, own, and govern cutting-edge AWS data platforms, ensuring scalability, resilience, security, and performance. You will define target-state architectures, integrate diverse services, and embed modern practices like GitOps and Data SRE for seamless operations.

Serve as the primary design authority for enterprise-wide AWS data platform initiatives. Define target-state architectures utilizing services such as AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, CloudWatch, and Lake Formation.

Own key architecture decisions encompassing scalability, resilience, security, governance, observability, performance, maintainability, FinOps, and production readiness. Develop platform standards, reference architectures, reusable frameworks, migration playbooks, and engineering governance for AWS data platforms.

Lead API-led and service-based integration patterns across various systems, including enterprise applications, SaaS platforms, data catalogs, governance tools, messaging services, and downstream analytics/AI consumers. Define standards for REST APIs, event-driven ingestion, CDC, streaming, file ingestion, database integration, authentication, retries, error handling, and dependency monitoring.

Establish Git connectivity across code repositories, define branching strategies, manage pull requests, conduct code reviews, implement release controls, and ensure artifact versioning and environment promotion. Lead CI/CD and Infrastructure-as-Code adoption using tools like GitHub, Azure DevOps, Jenkins, Terraform/OpenTofu, and CloudFormation.

Drive AWS security best practices, including IAM least privilege, KMS encryption, Secrets Manager, VPC endpoints, CloudTrail, and controlled data handling. Define governed access models using AWS Lake Formation, Glue Data Catalog, Macie, Immuta, Microsoft Purview, Collibra, and relevant enterprise IAM/access workflow tools.

Establish Data SRE practices for AWS data pipelines, lakehouse services, orchestration, ML/AI workloads, and platform operations. Define comprehensive observability dashboards covering job health, data freshness, data quality, SLA/SLO, cost, capacity, and incident trends.

Integrate AWS data platforms with Amazon SageMaker for data preparation, feature engineering, model training, deployment, and MLOps. Support AI/GenAI workloads using SageMaker, Bedrock, vector databases, and RAG patterns. Drive agentic and AI-assisted operations for tasks such as metadata discovery, lineage mapping, data quality rule generation, anomaly detection, and automated remediation.

This role requires a Guide or 10+ years of experience in data engineering, cloud data platforms, AI platforms, platform engineering, enterprise architecture, or delivery leadership. You must possess a strong, hands-on understanding of platform architecture, APIs, enterprise integration, Git/CI-CD, data security, governance, SRE operations, and AI/agentic engineering.

Ideal candidates will have preferred certifications aligned with cloud architecture, data engineering, DevOps, security, AI/ML, governance, and specific platform technologies. The role also benefits from individuals who act as trusted advisors to senior stakeholders, balancing strategic thinking with credible architecture and engineering discussions.

We are looking for professionals who can effectively manage strategy, delivery governance, team leadership, platform operations, and provide hands-on technology judgment. The ability to build future-ready, autonomous data engineering capabilities and mentor teams through emerging AI-native practices is highly valued.