Data Engineer – IFRS 17 at Jubilee Insurance

Job Ref. No. JLIL305

Role Purpose

We are seeking an experienced Data Engineer to join our team and lead the data integration, processing, and transformation efforts for our IFRS 17 implementation projects on Microsoft Azure. This role will involve close collaboration with actuarial, finance, and IT teams to ensure compliance with IFRS 17 reporting standards for Health and Life Insurance portfolios. The successful candidate will design and build efficient, scalable data pipelines within Azure and ensure endto-end data quality for IFRS 17 reporting requirements.

Main Responsibilities
Strategic Functions

• Cross-Functional Collaboration & Stakeholder Management
  • Working closely with actuarial, finance, risk, and IT teams to define data requirements, resolve challenges, and
  • deliver IFRS 17 reporting datasets on time.
  • Acting as the Azure data engineering subject matter expert, guiding best practices and processes within the IFRS 17 project team.
• Technical Innovation & Continuous Improvement
  • Optimizing database and data warehouse performance to support IFRS 17 analytics and reporting over the long term.
  • Identifying opportunities to enhance data workflows and infrastructure for scalability and efficiency.
• Alignment with IFRS 17 Compliance Goals
  • Collaborating with actuarial, finance, and accounting teams to ensure data solutions meet IFRS 17 reporting standards and timelines, contributing to regulatory compliance at a strategic level.
• Leadership in Data Engineering Practices
  • Guiding the team on Azure best practices, standards, and innovative approaches, positioning the organization for success in complex, data-driven projects beyond IFRS 17.

Operational Functions

• Azure Data Pipeline Development
  • Designing, building, and maintaining scalable data pipelines on Azure to ingest, transform, and store large datasets from multiple sources (e.g., policy administration systems, claims systems, finance systems).
  • Using Azure services like Azure Synapse Analytics to orchestrate and optimize data workflows for performance, reliability, and consistency.
• IFRS 17 Data Integration
  • Developing data mapping, transformation rules, and data models to support IFRS 17 methodologies for Health and Life Insurance products.
  • Ensuring data flows align with IFRS 17 reporting timelines and compliance standards.
• Data Quality & Governance
  • Implementing data validation checks, reconciliation processes, and governance frameworks to ensure accuracy,
  • completeness, and consistency of IFRS 17 data within the Azure Data Lake.
• Technical Implementation
  • Writing and optimizing Python scripts for data processing and ETL (Extract, Transform, Load) tasks.
  • Querying and processing data using SQL in Azure SQL Databases or Synapse.
  • Optimizing database performance (e.g., indexing, partitioning) in Azure Synapse or SQL Database.
• 5ocumentation
  • Developing and maintaining detailed documentation of data engineering processes, data flows, and transformation
  • logic to meet audit and regulatory requirements.
• Compliance & Security
  • Ensuring data handling processes comply with information security protocols, regulatory guidelines, and Azure cloud security best practices.

Corporate Governance

• Regulatory Compliance Oversight: Ensure all data engineering processes adhere to IFRS 17 reporting standards, audit requirements, and relevant financial regulations, safeguarding the organization’s legal and ethical obligations.
• Data Integrity and Accountability: Implement robust data validation, reconciliation, and governance frameworks within Azure to maintain accurate, complete, and consistent datasets, fostering trust in IFRS 17 reporting across stakeholders.
• Risk Mitigation through Security Practices: Uphold information security protocols and Azure cloud security best practices to protect sensitive insurance data, reducing risks related to breaches or non-compliance.
• Transparent Documentation and Reporting: Maintain comprehensive documentation of data flows, transformation logic, and processes, enabling traceability and supporting internal audits, regulatory reviews, and cross-functional accountability.

Leadership and Culture

• Fostering Cross-Functional Collaboration: Act as a bridge between technical and business teams (e.g., actuarial, finance, IT), promoting a culture of teamwork, mutual understanding, and shared goals in IFRS 17 projects.
• Empowering Knowledge Sharing: Share expertise in Azure data engineering and IFRS 17 processes through documentation and guidance, building team capability and encouraging a learning environment.
• Driving Accountability and Excellence: Uphold high standards of data quality and compliance, inspiring a culture of responsibility and precision that aligns with organizational values.
• Supporting Adaptability and Innovation: Contribute to a forward-thinking culture by introducing technical innovations and continuous improvements, helping the team adapt to evolving regulatory and business needs.

Key Competencies.

• Technical Proficiency in Azure and Programming: Expertise in Azure Synapse Analytics, Azure Data Lake, Python, and SQL to design and optimize data solutions for performance and scalability.
• Domain Knowledge of Insurance and IFRS 17: Strong understanding of Health and Life Insurance data structures and IFRS 17 requirements to align technical solutions with business and regulatory needs.
• Analytical and Problem-Solving Skills: Ability to analyze complex data challenges, identify solutions, and optimize workflows to meet IFRS 17 reporting demands efficiently.
• Stakeholder Collaboration and Communication: Effective communication and teamwork skills to collaborate with actuarial, finance, and IT teams, ensuring alignment and resolving data-related issues.

Key Deliverables

• Scalable Azure Data Pipelines: Design, build, and maintain efficient data pipelines on Azure to ingest, transform, and store large datasets from multiple sources, ensuring timely IFRS 17 reporting.
• IFRS 17 Data Integration Models: Develop data mappings, transformation rules, and models that align with IFRS 17 methodologies for Health and Life Insurance products, enabling accurate financial reporting. Data Quality and Governance Framework: Implement validation checks, reconciliation processes, and governance framewoks within the Azure Data Lake to ensure data accuracy, completeness, and consistency.
• Comprehensive Process Documentation: Create and maintain detailed documentation of data flows, transformation logic, and engineering processes to support audits, regulatory compliance, and team knowledge sharing.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related field

Relevant Experience

• 3+ years of experience as a Data Engineer or in a similar data-focused role.
• Proven track record of designing and delivering large-scale data solutions in complex environments, ideally in Azure.