Head, Data & AI Platforms, Architecture

Unum UK

. Define and own the multi-year enterprise data platform strategy and migration roadmap .

Posted 10/12/2026full-timeUnited StatesLead💰 $163,700 - $336,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in enterprise data platform strategy, AI governance, and multi-disciplinary team leadership, with a strong focus on data architecture, cloud FinOps, and compliance. Proven ability to translate technical strategies into business narratives and manage large-scale technology implementations.

Highest-signal resume keywords

Enterprise Data Platform StrategyAI Governance FrameworksCloud FinOps PracticesData Architecture and ModelingMLOps Tooling and Governance

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Applicant Tracking System Keywords

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Hard Skills

DatabricksSnowflakeMicrosoft EcosystemsData ModelingETL ToolsAI Capabilities DeliveryData GovernanceMLOpsAPI ArchitecturesLakehouse Design

Soft Skills

Executive CommunicationLeadershipTeam DevelopmentEngagement and RetentionPsychological Safety

Tools & Technologies

CI/CD PipelinesData Catalog ToolsData Management PlatformsBusiness Intelligence PlatformsInternal Data Marketplaces

Industry Keywords

Insurance Data DomainsRegulatory ComplianceModel Risk ManagementData ContractsSemantic Layers

Tech Stack

Tools & technologies

CloudETL

About the role

Key responsibilities & impact

Define and own the multi-year enterprise data platform strategy and migration roadmap
Establish reference architectures and standards for ingestion, storage, transformation, orchestration, serving, data contracts, schemas, and interoperability
Provide shared frameworks, templates, CI/CD pipelines, testing harnesses, and reusable components for data engineering teams
Own master and reference data management platforms
Ensure enterprise SLAs for platform availability, recovery, performance, scalability, and security-by-design
Own cloud and platform consumption models, FinOps practices, unit-cost trends, and total cost of ownership
Lead decommissioning of redundant data stores, ETL tools, reporting marts, and legacy reporting
Ensure platform controls and documentation satisfy audit, model risk, SOX ITGC, regulatory, and compliance requirements
Define and deliver the enterprise platform for building, deploying, orchestrating, and governing AI agents and GenAI applications
Evaluate and select AI platform capabilities across Databricks, Snowflake, Microsoft, and specialized vendors
Own lifecycle tooling for classical ML, GenAI, and agentic workloads, including feature stores, experiment tracking, registries, evaluation, deployment, monitoring, and red-teaming
Build and operate Responsible AI technical controls, including inventories, risk tiering, approvals, guardrails, logging, explainability, and bias testing
Own enterprise data catalog, lineage, policy, and access-governance tooling
Partner with business and product leaders to move agentic AI from pilot to production
Set standards for prompt-injection defense, data-leakage prevention, secure tool access, permissions, secrets management, and incident response
Maintain executive relationships with strategic partners and translate emerging technology into roadmap decisions
Own the enterprise BI and semantic-layer platform and certified datasets, metrics, performance, capacity, embedded analytics, and self-service enablement
Stand up and scale an internal data marketplace for governed, reusable data products, models, ML features, and AI assets
Provide secure, governed data-sharing capabilities for brokers, employers, TPAs, reinsurers, regulators, and partners
Serve as chief architect for enterprise data and AI target-state and transition architectures
Chair the Data & AI Architecture Review Board and ensure initiatives align with architecture standards
Own conceptual and logical data models for insurance domains
Partner with Enterprise Architecture, Application, and Integration teams on modernization and API programs
Evaluate technologies and vendors, run proofs of concept, and make build/buy/partner recommendations
Lead, inspire, and develop a multi-disciplinary organization through AVP/Director-level leaders
Design the operating model for central platforms, federated delivery teams, embedded architects, and partner functions
Own talent strategy, career paths, skills frameworks, upskilling, and external hiring
Instill platform-as-a-product, DevOps/DataOps/MLOps, documentation, post-mortems, inner-sourcing, reliability, and delivery-predictability practices
Set goals, conduct talent reviews, coach leaders, and build succession depth
Manage strategic platform vendors, system integrators, and managed-service providers
Foster an inclusive, psychologically safe environment and drive engagement and retention
Serve on the Data, Analytics & AI leadership team and advise the CIO, CDAO, business presidents, and functional heads
Translate technical strategy into business narratives and investment cases for executives, board committees, and investment councils
Own the platform portion of the enterprise data and AI investment portfolio
Represent Unum with industry bodies, analysts, and peer networks

Requirements

What you’ll need

Bachelor’s degree in computer science, Engineering, Information Systems, Mathematics, or a related field; master’s degree preferred
15+ years of progressive experience in data, analytics and technology
8+ years leading large, multi-disciplinary technology organizations
5+ years at a senior level (AVP or above) in an enterprise of comparable scale and complexity
Hands-on-credible expertise in at least two of Databricks, Snowflake, and Microsoft ecosystems
Experience leading an enterprise-scale implementation, migration, or consolidation
Experience delivering GenAI and/or agentic AI capabilities to production in a regulated enterprise
Experience with MLOps/LLMOps tooling, evaluation, monitoring, and governance controls
Deep understanding of enterprise, data, and AI architecture, conceptual/logical data modeling, integration patterns, lakehouse and warehouse design, event and API architectures, semantic layers, and LLM/autonomous-agent architecture
Experience establishing and operating AI governance and Responsible AI frameworks and technical controls
Experience working with Model Risk Management, Legal, and Compliance functions
Track record leading organizations of 10+ people through multiple management layers
Experience transforming workforce skills from legacy to modern platforms
Experience owning multi-million-dollar technology budgets, cloud FinOps, vendor negotiation, and business-case development
Exceptional executive communication with Boards, executives, regulators, and engineers
Preferred: insurance or financial-services experience and familiarity with insurance data domains and regulatory landscape
Preferred: data governance/catalog and MDM platforms
Preferred: enterprise BI platforms and internal data marketplaces/data-product operating models
Preferred: emerging agentic standards and AI offerings from Microsoft, Databricks, Snowflake, and model providers
Preferred: modernization from mainframe/on-premises warehouses to cloud platforms
Relevant certifications are a plus, not a substitute for demonstrated delivery
Preferred: global or multi-country technology organization and offshore/nearshore delivery experience

Benefits

Comp & perks

Onsite fitness facilities
Generous paid time off
Employee professional development programs
Healthcare benefits (health, vision, dental)
Short- and long-term disability insurance benefits
Performance-based incentive plans
401(k) retirement plan with employer match up to 5%
Additional 4.5% 401(k) contribution whether you contribute or not