Data Engineer
Description
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.
Responsibilities
- 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.
Requirements
- Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related field. (required)
- 3-4 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)
Benefits
- Comprehensive learning and development programmes.
- Innovative Performance Tool for regular, constructive feedback.
- Employee Assistance programme for you and your family.
- Free Daily Meals
- 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 socials