About the Job you are considering
Capgemini is seeking Data Management Specialist who can define strategy, operating models, and execution frameworks for enterprise data management across the end-to-end insurance value chain.
This is not a hands-on engineering role. Instead, the focus is on shaping the data agenda, defining target-state architectures, governance models, personas, and artefacts, and ensuring successful delivery of large-scale data programmes.
You will partner with business and technology leadership to establish data as a strategic asset, covering areas such as product master data, cataloguing, data quality, and governance frameworks across Policy, Claims, Underwriting, and Customer domains.
Hybrid Working
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home.
Your Role
Strategic Data Leadership
- Define and operationalize enterprise data management strategy across the insurance value chain
- Establish data operating models, including governance structures, roles, and responsibilities (data owners, stewards, custodians)
- Define personas and data consumption patterns across business functions (Underwriting, Claims, Finance, Distribution, Risk)
Data Management Frameworks
- Design and implement best practices for:
- Product master data management (MDM)
- Data cataloguing and metadata management
- Data quality frameworks (rules, KPIs, monitoring)
- Reference and master data standards
- Define standard artefacts such as:
- Data strategy and roadmap
- Data governance framework
- Data domain models
- Data lifecycle and lineage models
Programme & Delivery Leadership
- Lead large-scale programmes spanning:
- Data Lake / Data Warehouse / Lakehouse
- Analytics & BI platforms
- AI/ML enablement initiatives
- Manage multi-project portfolios across:
- Policy
- Claims
- Underwriting
- Customer data domains
- Drive alignment of data initiatives with business outcomes and KPIs
Stakeholder & Vendor Management
- Collaborate with business leaders, IT teams, and external vendors
- Translate insurance business requirements into data transformation initiatives
- Engage with platform providers (e.g., Guidewire, Duck Creek) to ensure seamless integration into data ecosystems
Governance, Risk & Compliance
- Establish and enforce data governance, quality, and compliance frameworks
- Ensure adherence to regulatory requirements:
- IRDAI
- Solvency II
- GDPR
- Define risk management and control frameworks for data programmes
Programme Management & Execution
- Manage budgets, timelines, dependencies, and risks
- Drive delivery using Agile / SAFe methodologies
- Provide governance oversight across multiple delivery streams
- Lead and coordinate cross-functional teams (architects, engineers, analysts, and business SMEs
Your Skills
- Strong hands-on experience with Databricks (must-have)
- Proficiency in Python and PySpark for large-scale data processing
- Solid understanding of data engineering fundamentals (ETL/ELT, batch processing, transformations)
- Proven experience building scalable and efficient data pipelines
- Exposure to Snowflake or modern cloud data warehouses
- Understanding of data architecture and system design principles
- Awareness of agentic AI and machine learning concepts, and how they integrate with data platforms
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