EY - GDS Consulting - AI And DATA - Databricks Architect - Senior 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 – Databricks Architect – Senior 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 capitalize 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.

The  Opportunity

The Senior Delivery Manager & Data Architect is a senior client-facing leader accountable for the end-to-end delivery and architectural integrity of complex data, analytics, cloud, and AI transformation programmes. The role combines delivery governance, commercial ownership, stakeholder leadership, and hands-on architecture oversight to translate business priorities into secure, scalable, reliable, and cost-effective data solutions.

The incumbent will act as the single point of accountability for delivery outcomes while defining target-state data architectures, engineering standards, governance controls, and transformation roadmaps. The role requires the ability to move confidently between executive discussions, programme governance, solution design, and technical assurance.

Your Key Responsibilities

• Own end-to-end delivery of large, multi-workstream data and analytics programmes from discovery and mobilisation through implementation, transition, and benefits realisation.
• Establish integrated plans, governance forums, delivery cadence, quality gates, dependency management, and executive reporting.
• Manage scope, schedule, budget, capacity, quality, risks, issues, assumptions, and change control; intervene early when delivery deviates from commitments.
• Drive Agile, Scrum, scaled Agile, or hybrid delivery practices appropriate to the client and programme context.
• Lead platform migrations, modernisation initiatives, releases, cutovers, hypercare, and transition to operations with clear readiness and acceptance criteria.
• Maintain delivery transparency using measurable outcomes, milestone health, financial performance, engineering metrics, and value-realisation indicators.
• Define enterprise data strategy, target-state architecture, reference architectures, transition states, and prioritised transformation roadmaps aligned to business and AI objectives.
• Architect modern cloud-native data platforms, including data lakes, lakehouses, warehouses, streaming solutions, data products, semantic layers, APIs, and analytical consumption patterns.
• Lead conceptual, logical, and physical data modelling using dimensional, relational, Data Vault, graph, ontology, and domain-oriented approaches as appropriate.
• Define integration and ingestion patterns for batch, near-real-time, event-driven, CDC, API, and file-based workloads.
• Evaluate platforms, products, and design alternatives; produce architecture decisions, solution blueprints, non-functional requirements, and implementation guardrails.
• Provide architecture assurance across the delivery lifecycle through design reviews, proofs of concept, engineering standards, performance reviews, and technical risk management.
• Ensure solutions meet requirements for scalability, resilience, availability, observability, interoperability, security, privacy, maintainability, and cost optimisation.
• Establish governance principles covering data ownership, stewardship, classification, lineage, metadata, master and reference data, retention, and policy enforcement.
• Embed data quality controls, reconciliation, auditability, privacy-by-design, role-based access, encryption, and regulatory compliance into solution architecture and delivery.
• Partner with cyber security, risk, legal, compliance, and operations teams to ensure controls are demonstrable and audit-ready.
• Build trusted relationships with C-suite sponsors, business leaders, product owners, technology executives, and delivery partners.
• Translate complex business needs into clear solution options, investment cases, roadmaps, and outcome-based delivery plans.
• Facilitate executive workshops, architecture forums, steering committees, and difficult decision-making conversations.
• Own or support proposals, solution shaping, estimates, statements of work, delivery models, contract assumptions, and commercial negotiations.
• Manage programme financials, forecasting, burn, margin, resourcing, vendors, and third-party commitments.
• Identify opportunities for account growth, reusable assets, accelerators, and follow-on transformation initiatives.
• Lead multidisciplinary teams of architects, data engineers, platform engineers, analysts, data scientists, DevOps specialists, quality engineers, and project managers.
• Set clear accountabilities, create a high-performance culture, mentor senior practitioners, and develop succession and capability plans.
• Promote engineering excellence, knowledge sharing, reusable patterns, continuous improvement, and responsible use of data and AI.
• Contribute to hiring, workforce planning, communities of practice, thought leadership, and organisational capability development.

Skills And Attributes for Success

• Bachelor’s or master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• Typically 15+ years of technology experience, including substantial experience delivering enterprise data programmes and operating in a lead data or solution architecture capacity.
• Demonstrable ownership of large, complex, multi-team programmes with responsibility for delivery governance, senior stakeholders, budgets, quality, and commercial outcomes.
• Strong experience designing and delivering cloud data platforms on Microsoft Azure, AWS, or Google Cloud; deep expertise in at least one ecosystem is essential.
• Proven experience with modern data platforms and technologies such as Microsoft Fabric, Azure Data Factory, Azure Databricks, Synapse Analytics, Snowflake, Databricks, Spark, Kafka, cloud object storage, and modern BI tools.
• Advanced knowledge of SQL and strong working understanding of Python or PySpark, data integration, distributed processing, DevOps, CI/CD, infrastructure automation, and observability.
• Solid command of data modelling, metadata management, data quality, master data management, governance, privacy, security, and lifecycle management.
• Experience architecting AI-ready data foundations and integrating machine learning, generative AI, vector, semantic, ontology, or knowledge graph capabilities is desirable.
• Excellent executive communication, consulting, negotiation, facilitation, decision-making, and conflict-resolution skills.

Ideally, you’ll also have

• Cloud architecture or data engineering certification in Azure, AWS, or Google Cloud.
• Microsoft Fabric, Databricks, or Snowflake certification.
• TOGAF, DAMA/CDMP, or an equivalent data or enterprise architecture credential.
• PMP, PRINCE2, SAFe, Scrum, or an equivalent programme or Agile delivery certification.
• ITIL certification is advantageous for roles with service transition or operational accountability.
• Delivery against agreed outcomes, milestones, budget, quality standards, and contractual commitments.
• Architecture compliance, reduction in technical debt, and adoption of reusable standards and patterns.
• Platform reliability, performance, security, data quality, observability, and unit-cost improvement.
• Stakeholder confidence, client satisfaction, benefits realisation, and successful adoption of delivered capabilities.
• Team engagement, capability growth, predictable staffing, and development of future technical and delivery leaders.
• Commercial performance, pipeline contribution, and expansion of trusted client relationships.

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 emphasizes 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.