Empowering Africa's tomorrow, together...one story at a time.
With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.
Job Summary We are seeking a highly skilled and motivated Data Engineer to join our team (Vehicle & Asset Finance MI) . The successful candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support analytics and business intelligence initiatives. You will work closely with data analysts, data scientists, and business stakeholders to ensure the availability, quality, and accessibility of data.
The successful candidate will support the increasing complexity and volume of data required for accurate and timely reporting. As the team continues to evolve and take on more strategic analytics and performance tracking initiatives, there is a growing need for robust, automated data pipelines and structured data models.
The Data Engineer will play a critical role in building and maintaining these pipelines, ensuring that data from various sources is ingested, transformed, and made available in a reliable and scalable format. This will enable the team to focus on analysis and insights rather than manual data preparation.
Additionally, the Data Engineer will support the development of reporting data marts, implement data quality and validation checks, and help integrate new systems or data sources into our reporting environment.
Their expertise will significantly enhance the team's ability to deliver trusted, automated, and actionable insights to the business.
Education and Experience Required:
Bachelor's Degree in one of the following fields (or equivalent experience): Computer Science, Information Systems, Data Science, Software Engineering
3-5 + years of experience in a data engineering or similar role
Proven experience with: Data pipeline development (ETL/ELT), Big data frameworks (e.g., Hadoop, Spark), Data integration from structured and unstructured sources
Preferred:
Honors or Master's degree in a relevant field will be advantageous.
AWS Certified Data Analytics
Microsoft Azure
Databricks
Skills Required:
Proficiency in programming (Python, SQL), cloud platforms (AWS, Azure, GCP), big data technologies (Hadoop, Spark), and data warehousing.
Data modeling, data integration, and ETL processes are also crucial.
Key areas of responsibility:
Data Engineering
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