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 1. 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 1. 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 1. 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 1. 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 s