Data Architect Insurance Domain

Wipro; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Wipro seeks an experienced Data Architect to define and deliver data architecture supporting risk, placement, broking, analytics, and operational data domains in the UK market.

The role requires strong London Market insurance domain expertise, designing scalable, governed data solutions and enabling trusted data across the technology landscape. Close collaboration with stakeholders is essential.

Qualifications

• Proven experience in data architecture for UK insurance domain and London Market knowledge.
• Design of scalable, governed data solutions across risk, placement, policy, claims, and analytics.
• Strong understanding of relational and NoSQL data platforms including MongoDB.
• Experience with cloud-based data platforms and distributed data architectures.
• Knowledge of data provenance, metadata, lineage, and data quality frameworks.
• Ability to translate business requirements into effective data architecture designs.

Responsibilities

• Define and maintain the target data architecture.

Skills

Data architecture

London Market domain

UK insurance market

Data modeling

Data governance

SQL

MongoDB

ETL/ELT

APIs

Event-driven architecture

Data integration

Cloud platforms

Data lakes/warehouses

Metadata & lineage

Stakeholder management

Communication

Tools

MongoDB

ETL tools

Job description

We are looking for an experienced Data Architect . This role will be responsible for defining and delivering data architecture that supports key business capabilities across risk, placement, broking, analytics, and operational data domains.

The successful candidate will bring strong data architecture expertise together with proven UK London Market insurance domain experience. They will play a leading role in shaping data strategy, designing scalable and governed data solutions, and enabling trusted, accessible data across the technology landscape.

This role requires close collaboration with business stakeholders, product teams, engineers, architects, and data governance teams to ensure data architecture supports both current business priorities and long-term strategic objectives.

Key Responsibilities

• Define and maintain the target data architecture
• Design scalable, secure, and resilient data solutions across operational and analytical environments.
• Create conceptual, logical, and physical data models to support core business processes and technology platforms.
• Partner with business and technology stakeholders to translate requirements into practical and effective data architecture designs.
• Lead the design of data structures and integration patterns supporting placement, policy, claims, exposure, and risk analytics use cases.
• Establish standards for data ingestion, transformation, storage, lineage, metadata, and consumption.
• Support the evolution of modern data platforms, including cloud-based data lakes, warehouses, and event-driven data architectures.
• Design data solutions across both relational and NoSQL technologies, including MongoDB where appropriate.
• Ensure alignment with enterprise architecture, security, privacy, regulatory, and governance standards.
• Drive improvements in data quality, consistency, stewardship, and reuse across the UK Risk Tech estate.
• Provide architectural oversight for integration between internal systems, market platforms, and third-party data providers.
• Support architecture governance, design reviews, and technology roadmaps.
• Identify opportunities to simplify the data landscape, reduce duplication, and improve data accessibility and trust.

Required Experience

• Proven experience within the UK insurance market, with strong London Market domain expertise.
• Strong understanding of London Market processes, participants, and data flows, including brokers, carriers, coverholders, and MGAs.
• Experience supporting data domains such as placement, policy, claims, exposure, bordereaux, and risk analytics.
• Strong knowledge of data integration patterns including ETL/ELT, APIs, event-driven architecture, and batch processing.
• Experience with modern cloud-based data platforms and distributed data architectures.
• Experience with both relational and non-relational data platforms, including exposure to MongoDB and document-based data models.
• Strong understanding of data governance, metadata, lineage, and data quality frameworks.
• Experience working across complex legacy and modern technology environments.
• Strong stakeholder management and communication skills, with the ability to engage effectively across business and technical teams.
• Data architecture and enterprise data design
• Conceptual, logical, and physical data modeling
• Data integration and interoperability
• SQL and strong understanding of relational databases
• Experience with NoSQL technologies, including MongoDB
• Knowledge of document-based and operational data models
• Data warehousing and/or data lake architecture
• Metadata, lineage, and data governance
• Cloud platforms such as Azure, AWS, or GCP
• Strong analytical, problem-solving, and communication skills