We are seeking a Data Engineer to support the delivery of enterprise data solutions aligned to the bank’s Data Architecture Roadmap.
This role focuses on building, maintaining, and optimising data pipelines and infrastructure, enabling advanced analytics, machine learning, and AI use cases across the organisation.
The successful candidate will play a key role in ensuring high-quality, reliable, and accessible data to support Nedbank’s journey toward becoming a data-driven organisation.
Key Responsibilities
1. Data Pipeline Development & Support
- Maintain and support data pipelines across:
- Data ingestion
- Data provisioning
- Data streaming
- API-based data services
- Monitor pipeline performance and ensure successful execution
- Implement minor enhancements and fixes to pipelines
- Support senior Data Engineers within data delivery initiatives (Epics)
2. Data Engineering Operations
- Perform day-to-day data-related tasks, including:
- Data profiling
- Data cleaning and transformation
- Data validation and quality assurance
- Data configuration and support
- Assist in building and maintaining basic data pipelines
3. Data Infrastructure Support
- Support and maintain data platforms and infrastructure
- Ensure systems are:
- Secure
- Available
- Reliable
- Monitor and support data warehouse environments
4. Data Warehouse Monitoring & Support
- Provide first-line support for data warehouse issues
- Monitor pipeline jobs and ensure SLA adherence
- Troubleshoot failures and ensure data availability
- Run daily operational checks and reporting
5. Cloud Data Platform Support
- Monitor and manage cloud-based data environments (compute & storage)
- Ensure cloud pipelines execute successfully
- Support cloud operations aligned to enterprise standards
6. Data Visualisation & Access
- Create and manage virtual databases
- Assist with generating data extracts for business users
- Support self-service data capabilities
7. Data Analysis & Documentation
- Collaborate with Data Analysts on:
- Data profiling
- Data validation
- Data documentation
- Ensure proper documentation of pipelines and data assets
8. Stakeholder Collaboration
- Work closely with business stakeholders to:
- Understand data requirements
- Improve query performance
- Optimise data usage
- Contribute to continuous improvement of data solutions
Minimum Requirements
Experience
- 3–6+ years’ experience in Data Engineering or related field
- Experience working in data warehouse or big data environments
- Exposure to banking or financial services (preferred)
Technical Skills
- Strong SQL skills
- Experience with:
- Data pipelines (ETL/ELT)
- Data ingestion and transformation
- Data quality and validation
- Exposure to:
- Cloud platforms (Azure / AWS preferred)
- Data warehousing technologies
- APIs and data integration
Nice to Have
- Experience with:
- Streaming technologies (e.g., Kafka)
- Data virtualisation tools
- Big data ecosystems
- Exposure to machine learning / AI data pipelines
- Understanding of data governance and security
Key Competencies
- Strong analytical and problem-solving skills
- Attention to detail and data quality focus
- Ability to work in Agile delivery environments
- Strong collaboration and stakeholder engagement skills
- Ability to operate in a fast-paced, enterprise environment
Environment
- Agile, squad-based delivery model
- Enterprise-scale data platforms
Why This Role?
- Exposure to enterprise data transformation initiatives
- Opportunity to work on AI, ML and advanced analytics enablement
- Contribute to building a modern, scalable data ecosystem within a leading bank
Desired Skills:
- Data Engineer
- Data Engineering
- ETL