Data engineer
Summary
Build and maintain ETL pipelines and cloud data platforms for a multi-tenant fintech data platform, ensuring secure, scalable data delivery and compliance with financial regulations.
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 company's 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. Requirements: Bachelor's 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 & Databases: Python, SQL, C#, Postgre SQL, Azure SQL and Relational & No SQL databases Data Engineering: ETL Development, Data Pipeline Development, Data Modelling, Data Warehousing, Data Integration and Data Quality & 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) Dev Ops and Tools: Azure Dev Ops, Git, Visual Studio, Visual Studio Code and Excel Advantageous: Cloud Data Certifications Experience within Financial Services or Fin Tech Exposure to regulated environments