Data Engineer at Dangote

The ideal candidate will have a strong background in data engineering, with proficiency in ETL/ELT processes, big data technologies, and cloud platforms. You will play a critical role in ensuring data accessibility, quality, and integrity by maintaining a scalable infrastructure that supports data analytics and other data-related initiatives. This position offers an exciting opportunity to work collaboratively with cross-functional teams and leverage your expertise to shape our data infrastructure.

Responsibilities

• Acts as the architect and builder of the data infrastructure, creating the necessary foundation for proper analytics engagements. 
• Design and implement efficient ETL (Extract, Transform, Load) pipelines to support data integration and analytics.
• Build and maintain data warehouses and data lakes to support business intelligence and related data applications.
• Develop data models and schemas for effective data analysis and reporting.
• Optimise data processing, query performance, and platform efficiency.
• Ensure data quality, integrity, and security through robust governance practices
• Lead data migration initiatives across multiple platforms.
• Modernise applications and databases to leverage Azure's advanced capabilities.
• Implement monitoring solutions for database usage, performance, and reliability.
• Develop automated data quality checks and testing procedures.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in a similar role within the technology industry.
• Proven experience in data engineering, with a strong foundation in ETL/ELT processes and data warehousing.
• Proven ability to work with both OLTP (Microsoft SQL Server/MySQL) and OLAP systems (Snowflake).
• Hands-on experience in designing, optimising, and managing batch and streaming data pipelines.
• Expertise in data migration and modernisation, particularly on Azure cloud platforms.
• Microsoft Certification in Azure Data Engineering is highly desirable.
• Expertise in SQL, Python, and other programming languages relevant to data engineering.
• Experience with big data technologies such as Hadoop, Spark, and Hive.
• Knowledge and hands-on experience with cloud platforms like AWS, Azure, or GCP, including services such as Azure Data Factory, Azure Synapse Pipeline, Azure Event Hub, and Azure IoT Hub.
• Familiarity with data visualisation tools like Power BI.
• On-site availability required