EY - GDS Consulting - AI And DATA -AI Data Platform Architect/Lead - Manager

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

EY-Consulting - Data and Analytics - AWS Data Platform Architect / Engineering Manager - / Manager / Lead Architect

EY's Consulting Services is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional and technical capabilities and product knowledge. EY's financial services practice provides integrated Consulting services to financial institutions and other capital markets participants, including commercial banks, retail banks, investment banks, broker-dealers & asset management firms, and insurance firms from leading Fortune 500 Companies. Within EY's Consulting Practice, Data and Analytics team solves big, complex issues and capitalise on opportunities to deliver better working outcomes that help expand and safeguard the businesses, now and in the future. This way we help create a compelling business case for embedding the right analytical practice at the heart of client's decision-making.

Role

AWS Data Platform Architect / Engineering Manager - Experience Guide

• Guide / 10+ years Primary Skill Area
• AWS Data Platforms, APIs, SageMaker, Data Security, Data SRE & Agentic Operations

The opportunity

Provide architecture leadership, platform ownership and delivery governance for enterprise-scale AWS Data & AI platforms. The role is responsible for shaping AWS data platform strategy, leading modernisation and migration programmes, defining reusable engineering standards, integrating APIs and enterprise services, establishing Git/CI-CD practices, embedding Data SRE, strengthening data security and enabling agentic/AI-assisted operations across AWS-native data platforms.

Your Key Responsibilities

• AWS strategy, architecture and platform ownership
• Serve as design authority for AWS data platform initiatives across multiple domains, programmes and enterprise data products.
• Define target-state architecture using AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, CloudWatch, Lake Formation and lakehouse patterns.
• Own architecture decisions for scalability, resilience, security, governance, observability, performance, maintainability, FinOps and production readiness.
• Create platform standards, reference architectures, reusable frameworks, migration playbooks and engineering governance for AWS data platforms.

APIs, service integration and AWS platform connectivity

• Lead API-led and service-based integration patterns across source systems, enterprise applications, SaaS platforms, data catalogues, 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.
• Integrate AWS data platforms with enterprise services such as IAM, secrets management, network controls, monitoring, ticketing, metadata, lineage, access workflows and DevOps tools.
• Drive reusable integration frameworks using API Gateway, Lambda, EventBridge, Step Functions, Glue, EMR, MWAA, Kinesis and managed event-driven patterns where appropriate.

Git connectivity, DevSecOps and platform automation

• Establish Git connectivity across code repositories, branching strategy, pull requests, code reviews, release controls, artefact versioning and environment promotion.
• Lead CI/CD and Infrastructure-as-Code adoption using GitHub, Azure DevOps, Jenkins, Terraform/OpenTofu, CloudFormation and policy-as-code practices.
• Define automated testing, code scanning, dependency scanning, secrets management, configuration management, deployment validation and production release documentation standards.
• Promote automation for environment setup, monitoring, reconciliation, deployment validation, compliance evidence and support handover.

Data security, Immuta and governed AWS access

• Drive AWS security practices including IAM least privilege, KMS encryption, Secrets Manager, VPC endpoints, CloudTrail, logging, controlled data handling and audit-ready access patterns.
• Define governed access models using AWS Lake Formation, Glue Data Catalog, Macie, Immuta, Microsoft Purview, Collibra and enterprise IAM/access workflow tools as relevant.
• Implement controls for RBAC/ABAC, dynamic masking, row/column-level access, data classification, lineage, data residency, privacy and policy enforcement.
• Partner with cyber, privacy, risk, infrastructure and architecture teams to ensure AWS platform designs are secure, compliant and production-ready.

Data SRE, observability and production operations

• Establish Data SRE practices for AWS data pipelines, lakehouse services, orchestration, ML/AI workloads and platform operations.
• Define observability dashboards covering Glue/EMR/MWAA job health, data freshness, data quality, SLA/SLO, cost, capacity, access activity, incident trends and dependency failures.
• Act as escalation point for complex production issues, root-cause analysis, recurring incident elimination, performance tuning and long-term platform improvement.
• Drive restartability, retry logic, alert rationalisation, runbooks, service transition, support operating model and operational continuity.

SageMaker, AI integration and agentic AWS operations

• Integrate AWS data platforms with Amazon SageMaker for data preparation, feature engineering, model training, deployment, model monitoring, MLOps and inference-ready data products.
• Support AI/GenAI workloads using SageMaker, Bedrock where relevant, vector databases, knowledge bases, RAG, GraphRAG, model evaluation and enterprise AI governance patterns.
• Drive agentic and AI-assisted operations for metadata discovery, mapping, lineage, data quality rule generation, anomaly detection, failure diagnosis, automated remediation and self-healing workflows.
• Ensure AI-enabled AWS data solutions remain secure, governed, explainable, observable and aligned with enterprise risk controls.

Skills And Attributes For Success

Skill / capability area - Details

• Core AWS platform - AWS Glue, Amazon S3, Athena, Redshift, EMR, MWAA/Airflow, Step Functions, Lambda, EventBridge, Kinesis, CloudWatch, Lake Formation.
• APIs and integration - REST APIs, API Gateway, Lambda integration, event-driven architecture, CDC, streaming, enterprise applications, workflow tools, downstream analytics and AI consumers.
• Git, DevSecOps and IaC -GitHub, Azure DevOps, Jenkins, Git connectivity, CI/CD, Terraform/OpenTofu, CloudFormation, policy-as-code, automated testing, deployment validation.
• Governance and security -- IAM, KMS, Secrets Manager, Lake Formation, Glue Data Catalog, Macie, CloudTrail, Immuta, Purview, Collibra, RBAC/ABAC, masking, lineage, audit.
• Reliability and operations - Data SRE, CloudWatch observability, SLA/SLO, incident management, root-cause analysis, runbooks, restartability, FinOps, capacity and cost governance.
• AI and agentic engineering - Amazon SageMaker, SageMaker Pipelines, Feature Store, Model Registry, Model Monitor, Bedrock, RAG, GraphRAG, vector databases, Agentic AI, LLMOps, AI governance.

To qualify for the role, you must have

• Relevant experience guide: Guide / 10+ years
• 10+ years in data engineering, cloud data platforms, AI platforms, platform engineering, enterprise architecture or delivery leadership.
• Strong hands-on understanding of platform architecture, APIs, enterprise integration, Git/CI-CD, data security, governance, SRE operations and AI/agentic engineering.
• Preferred certifications aligned to cloud architecture, data engineering, DevOps, security, AI/ML, governance and platform-specific technologies.

Ideally, you'll also have

• Acts as trusted advisor to senior stakeholders while staying credible in architecture and engineering discussions.
• Balances strategy, delivery governance, team leadership, platform operations and hands-on technology judgement.
• Comfortable building future-ready autonomous data engineering capability and mentoring teams through emerging AI-native practices.

What We Look For

• Acts as trusted advisor to senior stakeholders while staying credible in architecture and engineering discussions.
• Balances strategy, delivery governance, team leadership, platform operations and hands-on technology judgement.
• Comfortable building future-ready autonomous data engineering capability and mentoring teams through emerging AI-native practices.

What Working At EY Offers

At EY, we're dedicated to helping our clients, from start-ups to Fortune 500 companies, and the work we do with them is as varied as they are.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasises high quality and knowledge exchange. Plus, we offer:

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way that's right for you

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.