Data Engineer

As a Data Engineer within our Fintech ecosystem, you'll focus on building and maintaining the data pipelines and processes that power our financial analytics, reporting, and decision-making. You'll work with data from diverse systems—ranging from transactional platforms to customer engagement tools ensuring it is reliable, accessible, and optimized for high-impact use. This role is essential to support our transition to modern data practices, including cloud-native architectures and real-time processing, while maintaining the continuity and stability of our on-premises operations. Your work will directly enable smarter, faster financial services and help shape the future of data in Payments.

• Developing and maintaining data pipelines to support real-time and batch processing.
• Writing and optimizing SQL queries, stored procedures, and scripts for data processing.
• Supporting ETL/ELT workflows for data integration and transformation.
• Collaborating with team members to integrate data from various sources into centralized systems.
• Implementing and managing data streaming solutions using platforms like Kafka or RabbitMQ.
• Ensuring data quality and reliability across all pipelines and processes.
• Monitoring and troubleshooting data pipelines to ensure performance and reliability.
• Documenting data workflows and providing support for data-related issues.

• Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related field. (required)
• 2-4 years of experience in data engineering or related roles. (required)
• Strong SQL skills, including querying and optimizing database operations. (required)
• Experience developing data pipelines for real-time and batch processing. (required)
• Hands-on experience with data streaming platforms such as Kafka or RabbitMQ. (required)
• Familiarity with ETL processes and tools. (required)
• Proficiency in a programming language such as Python or Java for data tasks. (required)
• Knowledge of data modelling basics for relational databases. (required)
• Attention to detail and a commitment to ensuring data accuracy and reliability. (required)
• Problem-solving skills and the ability to troubleshoot issues in data systems. (required)
• Relevant certifications (e.g., AWS Certified Data Analytics Specialty, Microsoft Certified: Azure Data Engineer, or Databricks Certified Data Engineer). (preferred)
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and cloud-based data services. (preferred)
• Exposure to big data technologies such as Spark or Hadoop. (preferred)
• Exposure to Apache Spark, Airflow, Kafka (preferred)
• Knowledge of data governance and compliance standards. (preferred)
• Experience with data formats like JSON or Parquet. (preferred)
• Writing clean, modular code for data processing, automation, and integration with APIs or cloud services. (preferred)
• Basic understanding of containerization tools such as Docker. (preferred)
• Interest in learning and adopting emerging data technologies. (nice-to-have)

• We’re dedicated to your supergrowth. Our comprehensive learning and development programmes give you a range of resources and opportunities to expand your skills and advance your career.
• Your hard work and achievements won’t go unnoticed. Our innovative Performance Tool ensures you receive regular, constructive feedback, helping you to continuously improve and reach your full potential.
• Our Employee Assistance programme offers a variety of benefits which you and your family can benefit from.
• Free Massages On-site.
• Free On-Site Gym.
• Group Life Cover.
• Funeral Fund Benefit.
• Financial Services Assistance.
• Employee Assistance Programme.
• Curro School Fees Benefit.
• Income Continuation Benefit.
• Leadership Training.
• Referral Bonus.
• Medical Aid Subsidy.
• Free Sleep Coaching.
• On-site Barista.
• Retirement Annuity Subsidy.
• Team buildings.