Data & Analytics Engineer

Job Summary

• The Data & Analytics Engineering function is responsible for building and maintaining the data pipelines, models, and platforms that power the Enterprise Data Warehouse EDW and business intelligence initiatives.
• This role combines data engineering and analytics engineering to ensure that high-quality, well-modeled, and timely data is available for reporting, advanced analytics, and actuarial IFRS17 Reporting.

Responsibilities
Data Engineering:

• Maintain the Enterprise Data Warehouse EDW as a trusted single source of truth to support analytics, reporting, and advanced modeling.
• Design, build, and optimize ETL/ELT pipelines using Python, dbt, and Airflow for orchestration.
• Collect and load structured and unstructured data from internal and external systems.
• Manage the organization-wide data collection process for IFRS17, automating inputs from data stewards and producing monthly outputs for actuarial evaluations.
• Design and optimize dbt models, transforming raw data into analytics-ready datasets.
• Ensure data quality, accuracy, and integrity across all pipelines and reporting systems.
• Analyze the organization’s data maturity level, uncover gaps, and recommend improvements.
• Continually assess data quality, clean dirty data and raise concerns over gaps with closure recommendations
• Implement best practices for data governance, model testing, validation, and documentation.
• Ensure proper version control and CI/CD workflows using Git and Azure DevOps.
• Collaborate with analysts, actuaries, and business stakeholders to deliver actionable insights.
• Uphold data security and governance in collaboration with DBAs and system administrators.
• Assess new and existing data systems and continually uncover gaps to improve data maturity

Analytics Engineering:

• Develop, maintain, and optimize dbt models with tests, documentation, and version control.
• Translate business requirements into scalable data models that serve analytics and reporting needs.
• Support incremental data refreshes transformation logic to improve automation and scalability.
• Continuously monitor and troubleshoot data workflows within the warehouse for improvement.
• Create Machine learning models for predictive analytics
• Collaborate with business units to define KPIs, use cases, and reporting needs.
• Support the development of BI solutions using SSRS, SSIS, and SSAS.
• Enable Data Analysts and business stakeholders by providing well-structured, analytics-ready datasets.
• Provide technical guidance for predictive analytics and advanced statistical modeling.
• Supply Data models and insightful knowledge base to the AI system.

Requirements

• HND / B.Sc Degree in Computer Science or any related discipline.
• Knowledge of SQL & Python is an added advantage
• Minimum of 3 - 4 years experience.