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 - AI/Data Platform Engineering Manager - / Manager 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 : AI/Data Platform Engineering Manager Experience Guide : Guide / 10+ years Primary Skill Area : Enterprise Platforms: Databricks, Snowflake, MS Fabric & Autonomous Data Engineering The opportunity Lead enterprise-scale Data, AI, and Aladdin platform engineering programmes across Databricks, Snowflake, Microsoft Fabric, and cloud ecosystems. The Manager is accountable for solution strategy, delivery leadership, Aladdin integration and onboarding, stakeholder engagement, platform operating model, governance, data quality, security, service integration, Git-based engineering, SRE practices, AI/agentic enablement, and capability growth for modern data platforms. Your Key Responsibilities • Lead end-to-end delivery of enterprise data platform and Aladdin integration programs across cloud, big data, governance, analytics, and AI-enabled engineering ecosystems. • Drive data discovery, asset alignment, onboarding strategy, and integration planning for Aladdin inbound and outbound services, ensuring alignment with client requirements and BlackRock specifications. • Act as the primary liaison between clients, BlackRock, architects, business stakeholders, and engineering teams to conduct requirements workshops, data parity discussions, solution reviews, and delivery governance. • Define solution roadmaps, delivery milestones, operating models, and implementation strategies across Aladdin programs, including Early Look, Early Win, and subsequent onboarding phases. • Translate business requirements into scalable data engineering, integration, compliance, reporting, and platform solutions leveraging modern architectures including Lakehouse, Data Fabric, Semantic Layer, and AI-ready data platforms. • Lead the design and implementation of robust data pipelines, ingestion frameworks, APIs, workflow orchestration, scheduling, metadata-driven processing, and cross-platform integrations supporting Aladdin services. • Drive data quality, reconciliation, audit, compliance, and control frameworks to ensure data accuracy, completeness, traceability, regulatory adherence, and successful data parity outcomes. • Establish metadata-driven monitoring, observability, lineage, logging, operational reporting, and Data SRE practices to improve platform reliability, transparency, and operational resilience. • Oversee platform performance, Spark optimization, dependency management, workload scalability, production readiness, incident management, and root cause analysis for large-scale data processing environments. • Define and enforce engineering standards across Git, CI/CD, Infrastructure-as-Code, DevOps, automation, testing, deployment, release management, and environment governance. • Lead cloud deployment, application onboarding, infrastructure integration, security controls, and platform enablement across Azure, AWS, Microsoft Fabric, and enterprise technology ecosystems. • Drive data governance, privacy, security, access management, metadata management, lineage, auditability, and compliance requirements in partnership with architecture, risk, cyber, and regulatory stakeholders. • Evaluate and promote the adoption of AI, Agentic AI, Fabric, GenAI, and LLMOps capabilities to accelerate metadata discovery, documentation, data quality management, monitoring, operational efficiency, and intelligent data engineering workflows. • Identify opportunities to leverage automation, AI-assisted engineering, and reusable accelerators to simplify business processes, improve delivery efficiency, and enhance operational support models. • Manage delivery risks, dependencies, stakeholder expectations, issue resolution, and cross-functional coordination across multiple workstreams and client engagements. • Mentor teams, foster engineering excellence, and drive adoption of modern data platforms, Data & AI, and automation-led delivery practices. Skills And Attributes For Success Skill / capability area - Details • Data Platforms, Architecture & Integration - Databricks, Snowflake, Microsoft Fabric, Lakehouse Architectures, Data Warehouses, Data Lakes, Enterprise Platform Integration, Data Products, Semantic Data Solutions, Modern Data Ecosystems. • Aladdin & Investment Data Platforms - BlackRock Aladdin Integration, Data Onboarding, Asset Alignment, Data Discovery, Data Parity Validation, Reconciliation, Compliance & Reporting Processes, Investment Data Management, Inbound and Outbound Data Services. • Platform Strategy & Delivery Leadership - Platform Roadmaps, Operating Models, Delivery Governance, Stakeholder Management, Enterprise Architecture Alignment, Risk Management, Production Readiness, Technical Leadership and Capability Development. • AI, GenAI & Agentic Enablement - Cortex AI, Databricks AI/BI & Genie, Mosaic AI, Fabric Copilot, Azure AI Foundry, RAG, Graph RAG, Agentic AI, LLMOps, AI Governance, Responsible AI, AI-enabled Engineering and Automation. • Engineering & Integration - APIs, Data Integration Patterns, Event-Driven Architectures, CDC, Git, CI/CD, Infrastructure-as-Code, Automation Frameworks, Release Management, Solution Design and Architecture Reviews • Cloud & DevOps - Azure, AWS, GCP, Terraform/Open Tofu, Kubernetes, Docker, Azure DevOps, GitHub Actions, Jenkins, Policy-as-Code, Platform Automation, Enterprise Scheduling and Orchestration Solutions. • Governance, Security & Reliability - RBAC/ABAC, Immuta, Microsoft Purview, Collibra, Data Classification, Lineage, Audit Controls, Data Privacy, Regulatory Compliance, Data Quality, Observability, Data SRE, FinOps, Platform Reliability • Client & Stakeholder Management - Requirements Workshops, Data Parity Discussions, BlackRock Engagement, Business & Technology Alignment, Cross-Platform Coordination, Delivery Planning, Dependency Management and Executive Communication. 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. • Experience delivering investment data platform integrations, including data onboarding, data parity, reconciliation, compliance/reporting workflows, and preferably BlackRock Aladdin inbound/outbound data integration solutions. • 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 stak