AAR Insurance is a licensed financial services provider in Kenya and a member of the Association of Kenya Insurers (AKI) with presence across the country through its intensive branch and broker network.

Reporting to the Group Head of Technology, the AI & Data Transformation Lead is the strategic and technical guide of the section, combining deep domain knowledge of reinsurance with expertise in programming, AI usage, business analysis methodologies, and enterprise process transformation and automation.

The AI & Data Transformations Lead will also design and operate secure, reliable, and scalable data platforms that support AAR Insurance Kenya Ltd operations in Kenya and that of its subsidiaries. The role enables claims analytics, fraud detection, regulatory reporting, actuarial analysis, and operational dashboards, while ensuring data quality and compliance.

Responsibilities or duties

• Lead business analysis across all 18+ departments to map current-state processes, identify pain points, design future-state automated workflows and drive their implementation.
• Develop and maintain the organization's AI roadmap, including use-case identification, feasibility analysis, and phased deployment.
• Engage with external partners, brokers, and technology vendors to benchmark transformation initiatives against global best practice.
• Mentor the Transformation Officer and coordinate ICT resource requests (servers, databases, APIs, cloud compute).
• Data Quality, Security & Governance:
• Implement data quality checks, validation rules, and anomaly detection.
• With support from the Systems Administrators, enforce secure data access using IAM, encryption, and role-based controls.
• Ensure compliance with Kenya Data Protection Act (2019) and healthcare confidentiality standards.
• Assess AI-related risks (model bias, data drift, explainability, regulatory non-compliance) and recommend mitigation controls.
• Review and recommend updates to Standard Operating Procedures (SOPs) to accommodate AI-driven decision support and automated processes.
• Chair the monthly Data Lock and Backup process, ensuring immutable snapshots are captured at midnight on the last day of each month.
• Data Engineering
• Data Pipeline & Streaming Engineering:
• Design and implement real-time and batch data pipelines from insurance core systems and microservices.
• Build and operate event-driven data flows using Kafka (Confluent) and Amazon SQS.
• Support near-real-time processing for claims, authorizations, payments, and member events.
• Data Modelling & Schema Management:
• Design and maintain insurance and healthcare data models (members, policies, benefits, claims, providers, payments).
• Oversee the design of standard data tables, master data dictionaries, and unified access frameworks for cross-departmental analytics. Manage database schema changes using Liquibase.
• Ensure data consistency, reconciliation, and controlled schema evolution.
• Cloud Data Architecture:
• Build and manage AWS-based data platforms, including data lakes and analytics layers.
• Support downstream use cases including BI reporting, actuarial modelling, and AI/ML initiatives.
• Optimize data pipelines for performance, scalability, and cost.
• Monitoring, Documentation & Collaboration:
• Monitor data pipelines using Datadog.
• Document data flows, schemas, and integration points.
• Collaborate with API teams using OpenAPI standards where data services are exposed.
• Continuity solutions based on data lakes & AI agents:
• Design and drive implementation of Group data-lake-based continuity solutions for East Africa, covering all core business data (members, policies, pricing, benefits, claims, providers, payments).
• Work with internal and external specialists to develop AI agents that support data validation, anomaly/fraud detection and automation of operational workflows, and accelerate migration or re-platforming by reconstructing
• NB: This job description is subject to review by management from time to time to align with business needs.

Qualifications or requirements

• Strong experience with Kafka, streaming architectures, and SQL.
• Experience building cloud data platforms on AWS.
• Understanding of insurance and healthcare data operational domains.
• Strong programme leadership and stakeholder management skills; able to drive complex, multi-country initiatives and manage senior stakeholders.
• Strong risk and continuity mindset; thinks in scenarios and contingencies, not only in day-to-day operations.
• Ability to operate within agile, product-aligned teams.
• Strong collaboration with security, compliance, underwriting, claims, and operations teams.
• High attention to data confidentiality, system reliability, and regulatory compliance.
• Strong communication skills suited to the Kenya insurance and healthcare market.
• Excellent communication and presentation skills; comfortable interacting with Group and local C-level executives, regulators and auditors, technical teams and business users across countries, investors and external partners.

Experience needed

7 years

• Lead business analysis across all 18+ departments to map current-state processes, identify pain points, design future-state automated workflows and drive their implementation.
• Develop and maintain the organization's AI roadmap, including use-case identification, feasibility analysis, and phased deployment.
• Engage with external partners, brokers, and technology vendors to benchmark transformation initiatives against global best practice.
• Mentor the Transformation Officer and coordinate ICT resource requests (servers, databases, APIs, cloud compute).
• Implement data quality checks, validation rules, and anomaly detection.
• With support from the Systems Administrators, enforce secure data access using IAM, encryption, and role-based controls.
• Ensure compliance with Kenya Data Protection Act (2019) and healthcare confidentiality standards.
• Assess AI-related risks (model bias, data drift, explainability, regulatory non-compliance) and recommend mitigation controls.
• Review and recommend updates to Standard Operating Procedures (SOPs) to accommodate AI-driven decision support and automated processes.
• Chair the monthly Data Lock and Backup process, ensuring immutable snapshots are captured at midnight on the last day of each month.
• Design and implement real-time and batch data pipelines from insurance core systems and microservices.
• Build and operate event-driven data flows using Kafka (Confluent) and Amazon SQS.
• Support near-real-time processing for claims, authorizations, payments, and member events.
• Design and maintain insurance and healthcare data models (members, policies, benefits, claims, providers, payments).
• Oversee the design of standard data tables, master data dictionaries, and unified access frameworks for cross-departmental analytics. Manage database schema changes using Liquibase.
• Ensure data consistency, reconciliation, and controlled schema evolution.
• Build and manage AWS-based data platforms, including data lakes and analytics layers.
• Support downstream use cases including BI reporting, actuarial modelling, and AI/ML initiatives.
• Optimize data pipelines for performance, scalability, and cost.
• Monitor data pipelines using Datadog.
• Document data flows, schemas, and integration points.
• Collaborate with API teams using OpenAPI standards where data services are exposed.
• Design and drive implementation of Group data-lake-based continuity solutions for East Africa, covering all core business data (members, policies, pricing, benefits, claims, providers, payments).
• Work with internal and external specialists to develop AI agents that support data validation, anomaly/fraud detection and automation of operational workflows, and accelerate migration or re-platforming by reconstructing

• Kafka
• Streaming architectures
• SQL
• AWS
• Business analysis methodologies
• Enterprise process transformation and automation
• Programming
• AI usage
• Data Quality, Security & Governance
• Data Engineering
• Data Pipeline & Streaming Engineering
• Data Modelling & Schema Management
• Cloud Data Architecture
• Monitoring, Documentation & Collaboration
• Continuity solutions based on data lakes & AI agents
• Programme leadership
• Stakeholder management
• Risk and continuity mindset
• Agile methodologies
• Collaboration
• Communication skills
• Presentation skills

• Bachelor of Science in Information Technology, Computer Science or a related field, or equivalent experience
• Confluent Certified Developer for Apache Kafka
• Databricks Data Engineer
• Master’s degree in Data Science/Analytics
• AWS Certified Data Analytics
• AWS Certified Solutions Architect Associate
• Google Professional Data Engineer