Data Engineer at FMN Holdings - Flour Mills of Nigeria Plc

FMN Holdings is recruiting a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power enterprise reporting, analytics, and AI initiatives across the Group.

What it offers

• Opportunity to work with Microsoft Azure Data Factory, Microsoft Fabric, OneLake, and Delta technologies to build and optimize data pipelines and Lakehouse architectures.
• Role involves designing and maintaining ETL/ELT pipelines, integrating data from ERP systems (AX 2012, D365), SQL databases, APIs, and third-party platforms.
• Focus on ensuring high system reliability through monitoring, troubleshooting, and resolving data processing issues.
• Collaboration with business analysts, data teams, and stakeholders to translate business requirements into technical data solutions.

Who can apply

• Candidates must possess a HND or Bachelor's Degree in Computer Science, Information Technology, Data Science, Engineering, or a related discipline.
• Minimum of 3–6 years' experience in Data Engineering, Data Integration, Data Warehousing, or Data Platform Development.
• Strong expertise in data engineering, data integration, and cloud-based data platforms is required.
• Advanced proficiency in SQL, Azure Data Factory, Microsoft Fabric, APIs, and data modelling techniques is essential.
• Strong analytical and problem-solving skills, with the ability to identify and resolve complex data quality issues.

What you'll do

• Design, develop, and maintain ETL/ELT pipelines using Microsoft Azure Data Factory and Microsoft Fabric.
• Integrate data from ERP systems (AX 2012, D365), SQL databases, APIs, and third-party platforms into centralized data environments.
• Implement and manage Lakehouse architectures using Microsoft Fabric, OneLake, and Delta technologies.
• Monitor data pipeline performance, troubleshoot failures, and resolve data processing issues to ensure high system reliability.
• Develop and maintain scalable data models that support business intelligence, analytics, and reporting requirements.
• Ensure data quality by implementing validation checks, cleansing processes, and governance controls across all data sources.
• Apply DevOps best practices including CI/CD, version control, automated deployments, and code management.
• Collaborate with business analysts, data teams, and stakeholders to translate business requirements into technical data solutions.