Lead Data consultant/Head of Data

Data Consultant role

5-6 years of Insurance domain experience.

Horsham , UK & Hybrid model

Job Description: Data Consulting Lead – Insurance (Data Architecture, Data Products & AI Platforms

)Role Summar

ySenior Data Consulting Lead with deep expertise in Data Architecture, Data Products, and AI-led Platforms, specialising in Insurance (with focus on Specialty Lines). This role drives enterprise-scale data and AI transformation, shaping modern data ecosystems, AI platforms, and AI-driven migration strategies on Azure, Databricks, and Power BI. A recognised thought leader, responsible for influencing C-level stakeholders, defining strategy, and delivering measurable outcomes through data + AI convergence

.Key Responsibilitie

s1. Data Strategy, AI Vision & Thought Leadershi

• pDefine enterprise-wide data and AI strategy aligned to business and regulatory prioritie
• sAct as a trusted advisor to CIO/CDO/AI leadership, shaping data & AI transformation roadmap
• sDrive data product thinking with embedded AI/ML capabilities (intelligent underwriting, claims automation, pricing optimisation
• )Bring market perspective on AI-native data ecosystems, GenAI enablement, and agentic architectures

2. Data & AI Architecture Leadershi

• pOwn end-to-end architecture across data and AI layers
• :Data ingestion, processing, modelling, semantic layer, and consumptio
• nAI platform integration (model lifecycle, feature engineering, inference pipelines
• )Design modern Lakehouse + AI architecture leveraging Azure and Databrick
• sDefine architecture for scalable, governed, and reusable AI-ready data platform
• sEnsure integration of data governance, lineage, security, and responsible AI principles

3. AI Platforms & AI-led Data Migratio

• nDesign and implement AI Platforms integrating
• :Model development environments, MLOps pipelines, feature stores, and model servin
• gLead AI-driven migration strategies, including
• :Automated schema discovery, data mapping, and transformation using AI accelerator
• sAI-assisted code conversion (e.g., legacy ETL → modern pipelines
• )Intelligent data quality assessment and anomaly detectio
• nDrive adoption of AI-enabled accelerators to
• :Reduce migration timeline
• sImprove accuracy and minimise manual interventio
• nEnable continuous intelligence through pipelines that combine data engineering with AI/ML workflow

s4. Insurance Domain & Data Product

• sDeep understanding of Specialty Lines insurance (Commercial, Marine, Liability, etc.
• )Define and operationalise domain-centric data products, such as
• :Risk profiling and underwriting intelligenc
• eClaims analytics and fraud detection model
• sPricing optimisation model
• sCustomer and broker analytics platform
• sAlign data products to business outcomes, regulatory compliance, and monetisation opportunities

5. Technology Leadership (Azure + Databricks + Power BI

• )Lead architecture and execution of
• :Azure Data Platform (ADF, Synapse, Fabric, ADLS
• )Databricks (Lakehouse, Delta, ML workflows, PySpark pipelines
• )Power BI (semantic models, enterprise dashboards, self-service BI
• )Drive adoption of
• :Metadata-driven architecture
• sAutomation, orchestration, and reusable framework
• sEnsure separation and optimisation of data engineering, analytics, and AI workloads

6. Consulting & Delivery Leadershi

• pLead end-to-end consulting engagements (Discovery → Architecture → Delivery → Value Realisation
• )Run executive workshops on Data Strategy, AI adoption, and operating model
• sDefine target operating models (Data + AI CoE, Data Product organisation
• )Mentor teams across architecture, engineering, analytics, and A
• IBuild reusable accelerators and GTM offerings in data + AI transformation

Required Experience & Skill

sCore Experienc

• e12–18+ years across Data, Analytics, AI Platforms, and Architectur
• eProven leadership of large-scale data and AI transformation programme
• sStrong experience in consulting, stakeholder engagement, and solution shapin

gInsurance Expertis

• eStrong domain expertise in Insurance (with exposure to Specialty Lines
• )Understanding of underwriting, claims, pricing, regulatory reporting data model
• sExperience mapping data products to insurance business capabilitie

sAI & Data Platform Expertis

• eExperience designing and implementing
• :AI/ML platforms (MLOps, model lifecycle management, feature stores
• )AI-enabled data pipelines and intelligent automation framework
• sExposure to
• :GenAI / LLM use cases in data (RAG, knowledge graphs, copilots
• )AI-driven migration and code/data modernisation approache

sTechnical Expertis

• eStrong hands-on / architectural expertise in
• :Azure data ecosystem (ADF, Synapse, Fabric, ADLS
• )Databricks (Delta Lake, Spark, ML workflows
• )Power BI (enterprise analytics & semantic layer
• )Strong grounding in
• :Data modelling (dimensional, domain-driven
• )Data governance, lineage, cataloguin
• gIntegration patterns (batch, streaming, APIs

)Leadership & Consulting Skill

• sExecutive stakeholder engagement (CIO/CDO/AI leaders
• )Ability to translate business problems into data + AI solution
• sStrong storytelling and influencing capabilit
• yExperience building data/AI CoEs and scalable delivery model