Data and Analytics Engineer
AIICO Insurance Plc
Job Details
Job Description
AIICO Insurance Plc was established in 1963 and is a financial services group listed on the Nigerian Exchange (NGX). The company operates across several business areas, including insurance, health maintenance and asset management.
AIICO Insurance Plc is seeking a skilled Data and Analytics Engineer to support its enterprise data infrastructure, business intelligence initiatives and advanced analytics capabilities. The successful candidate will help ensure that reliable, accurate and well-structured data is available for business reporting, predictive analytics and actuarial reporting.
Role Overview
The Data and Analytics Engineer will design, build, maintain and optimise data pipelines, data models and platforms that support the company's Enterprise Data Warehouse (EDW) and business intelligence operations.
The role combines data engineering and analytics engineering, with responsibilities covering data integration, transformation, quality assurance, governance and predictive modelling. The successful candidate will also support the collection and processing of data for IFRS 17 actuarial reporting and work closely with analysts, actuaries, developers and business stakeholders to deliver reliable data solutions.
Key Responsibilities
Data Engineering and Pipeline Management
- Maintain the Enterprise Data Warehouse as a reliable central source of data for reporting, analytics and advanced modelling.
- Design, develop and optimise ETL and ELT pipelines using Python, dbt and Apache Airflow.
- Collect, integrate and load structured and unstructured data from internal and external systems.
- Manage organisation-wide data collection for IFRS 17 reporting by automating inputs from data stewards and producing monthly outputs for actuarial evaluations.
- Develop and optimise data transformation processes to convert raw data into reliable, analytics-ready datasets.
- Monitor data pipelines and resolve issues affecting data availability, accuracy and performance.
- Identify data quality problems, investigate missing or inconsistent information and recommend corrective actions.
- Assess the organisation's data maturity, identify gaps and recommend improvements to existing systems and processes.
Analytics Engineering and Data Modelling
- Develop, maintain and optimise dbt models, including appropriate testing, documentation and version control.
- Translate business requirements into scalable data models for reporting and analytics.
- Implement incremental data refreshes and improve transformation logic to support automation and scalability.
- Monitor and troubleshoot data workflows within the data warehouse.
- Develop machine learning models to support predictive analytics.
- Provide technical guidance for predictive analytics and advanced statistical modelling.
- Build and maintain data models and knowledge resources that support AI systems.
- Provide analysts and business stakeholders with well-structured datasets for reporting and decision-making.
Business Intelligence and Reporting
- Support the development and maintenance of business intelligence solutions using SQL Server Reporting Services (SSRS), SQL Server Integration Services (SSIS) and SQL Server Analysis Services (SSAS).
- Work with business units to define key performance indicators, analytical use cases and reporting requirements.
- Support the delivery of data solutions that provide useful insights into business performance.
- Collaborate with analysts, actuaries and other stakeholders to meet reporting and analytical needs.
- Ensure data outputs support accurate and timely business and actuarial reporting.
Data Quality, Governance and Security
- Implement data governance practices, model testing, validation procedures and technical documentation.
- Maintain data accuracy, consistency and integrity across pipelines, models and reporting systems.
- Establish and maintain version control and continuous integration and delivery workflows using Git and Azure DevOps.
- Work with database administrators and system administrators to maintain data security and governance.
- Regularly assess existing data systems, identify weaknesses and recommend measures to improve data quality and maturity.
Requirements
Interested candidates should meet the following requirements:
- A Higher National Diploma or Bachelor's degree in Computer Science or a related discipline.
- A minimum of three to four years of relevant professional experience.
- Knowledge of SQL and Python is an advantage.
- Ability to work with data pipelines, data transformation processes and analytical data models.
- Strong analytical, troubleshooting and problem-solving skills.
- Ability to identify data quality issues and recommend practical solutions.
- Good communication and collaboration skills for working with technical teams, actuaries, analysts and business stakeholders.
Technical Skills and Tools
The role involves working with several data engineering, analytics and business intelligence technologies, including:
- Programming and querying: Python and SQL
- Data transformation: dbt
- Workflow orchestration: Apache Airflow
- Data platforms: Enterprise Data Warehouse systems
- Business intelligence: SSRS, SSIS and SSAS
- Version control and deployment: Git and Azure DevOps
- Advanced analytics: Machine learning and predictive modelling
- Data governance: Data quality testing, validation, documentation and security