Data Engineer

Our client is looking for a Data Engineer to join their growing technology team supporting a multi-tenant financial services data platform in Bryanston GP. This role is ideal for someone with a passion for building reliable secure and scalable data solutions while working alongside analytics product risk and compliance teams.

You will play a key role in developing and maintaining data pipelines ensuring high-quality data delivery and supporting the ongoing enhancement of the companys cloud-based data platform.

Responsibilities:

• Build maintain and optimize ETL pipelines that ingest data from APIs databases and event-driven sources.
• Develop and maintain Data Platform APIs to enable reliable data ingestion and access.
• Implement tenant-specific configurations while adhering to established naming conventions.
• Apply tenant-level data isolation using schemas partitions and access controls.
• Build and maintain reporting and analytics data models using existing templates and shared standards.
• Monitor scheduled pipelines troubleshoot failures and resolve data quality issues.
• Maintain daily and incremental data warehouse loads.
• Assist with onboarding new clients by validating source data and testing pipeline outputs.
• Work closely with senior data engineers to implement best practices for multi-tenant architecture.
• Collaborate with analytics product and customer-facing teams to understand reporting requirements.
• Support regulatory and audit requirements by following data governance retention and audit standards.
• Handle sensitive financial and personal information (PII) in accordance with POPIA and company policies.
• Implement security best practices including role-based access control encryption masking and least-privilege access.

• Bachelors Degree in:
  • Data Science
  • Computer Science
  • Information Technology
  • Or a related field
• Minimum 2 years experience as a Data Engineer or in a similar technical role.
• Experience building and maintaining ETL pipelines.
• Working knowledge of cloud-based data platforms.
• Experience with relational and non-relational databases.
• Exposure to data warehousing concepts and best practices.
• Programming and Databases: Python SQL C# PostgreSQL Azure SQL and Relational and NoSQL databases
• Data Engineering: ETL Development Data Pipeline Development Data Modelling Data Warehousing Data Integration and Data Quality and Validation.
• Cloud Tech: Azure Data Factory Azure Synapse Analytics Azure Data Lake Gen2 Azure Blob Storage Azure Web Apps Azure Entra ID Azure Key Vault and RBAC (Role-Based Access Control)
• DevOps and Tools: Azure DevOps Git Visual Studio Visual Studio Code and Excel

Advantageous:

• Cloud Data Certifications
• Experience within Financial Services or FinTech
• Exposure to regulated environments