Role Summary
Senior 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 Responsibilities
1. Data Strategy, AI Vision & Thought Leadership
- Define enterprise-wide data and AI strategy aligned to business and regulatory priorities
- Act as a trusted advisor to CIO/CDO/AI leadership, shaping data & AI transformation roadmaps
- Drive 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 Leadership
- Own end-to-end architecture across data and AI layers:
- Data ingestion, processing, modelling, semantic layer, and consumption
- AI platform integration (model lifecycle, feature engineering, inference pipelines)
- Design modern Lakehouse + AI architecture leveraging Azure and Databricks
- Define architecture for scalable, governed, and reusable AI-ready data platforms
- Ensure integration of data governance, lineage, security, and responsible AI principles
3. AI Platforms & AI-led Data Migration
- Design and implement AI Platforms integrating:
- Model development environments, MLOps pipelines, feature stores, and model serving
- Lead AI-driven migration strategies, including:
- Automated schema discovery, data mapping, and transformation using AI accelerators
- AI-assisted code conversion (e.g., legacy ETL → modern pipelines)
- Intelligent data quality assessment and anomaly detection
- Drive adoption of AI-enabled accelerators to:
- Reduce migration timelines
- Improve accuracy and minimise manual intervention
- Enable continuous intelligence through pipelines that combine data engineering with AI/ML workflows
4. Insurance Domain & Data Products
- Deep understanding of Specialty Lines insurance (Commercial, Marine, Liability, etc.)
- Define and operationalise domain-centric data products, such as:
- Risk profiling and underwriting intelligence
- Claims analytics and fraud detection models
- Pricing optimisation models
- Customer and broker analytics platforms
- Align 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 architectures
- Automation, orchestration, and reusable frameworks
- Ensure separation and optimisation of data engineering, analytics, and AI workloads
6. Consulting & Delivery Leadership
- Lead end-to-end consulting engagements (Discovery → Architecture → Delivery → Value Realisation)
- Run executive workshops on Data Strategy, AI adoption, and operating models
- Define target operating models (Data + AI CoE, Data Product organisation)
- Mentor teams across architecture, engineering, analytics, and AI
- Build reusable accelerators and GTM offerings in data + AI transformation
Required Experience & Skills
Core Experience
- 12–18+ years across Data, Analytics, AI Platforms, and Architecture
- Proven leadership of large-scale data and AI transformation programmes
- Strong experience in consulting, stakeholder engagement, and solution shaping
Insurance 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
s
AI & Data Platform Experti
- seExperience designing and implementin
- g:AI/ML platforms (MLOps, model lifecycle management, feature store
- s)AI-enabled data pipelines and intelligent automation framewor
- ksExposure t
- o:GenAI / LLM use cases in data (RAG, knowledge graphs, copilot
- s)AI-driven migration and code/data modernisation approach
es
Technical Expert
- iseStrong hands-on / architectural expertise
- in:Azure data ecosystem (ADF, Synapse, Fabric, AD
- LS)Databricks (Delta Lake, Spark, ML workflo
- ws)Power BI (enterprise analytics & semantic lay
- er)Strong grounding
- in:Data modelling (dimensional, domain-driv
- en)Data governance, lineage, catalogu
- ingIntegration patterns (batch, streaming, AP
Is)Leadership & Consulting Ski
- llsExecutive stakeholder engagement (CIO/CDO/AI leade
- rs)Ability to translate business problems into data + AI soluti
- onsStrong storytelling and influencing capabil
- ityExperience building data/AI CoEs and scalable delivery mod