EY - GDS Consulting - AI And DATA - Databricks Architect - Sr Manager

EY-Consulting - Data and Analytics - Databricks Architect - Senior Manager

Job Summary

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.

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 practitione…