DATA ENGINEER
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Summary
Data engineer at a well-established South African group of companies, building and maintaining ETL pipelines, data platform APIs, and warehouse models for a multi-tenant platform handling financial/PII data under regulations like POPIA. Core stack: Python, SQL, cloud-hosted data platforms, CI/CD, and relational/non-relational databases.
Our client, a well-established group of companies, is looking for a Data Engineer with strong analytics skills (including problem-solving, understanding data characteristics, identifying patterns, and addressing data quality issues). This is the ideal position for someone who wants to build their career with a company with an excellent reputation.
Formal Education
- Degree in Data Science, Information Technology, Computer Science or equivalent.
Advantageous
- Cloud Data Certifications.
- Exposure to regulated environments, financial services, and fintech.
Experience
- Minimum of 2 years in a data engineer role or a similar technical role.
Responsibilities
- Build and maintain ETL pipelines supporting a multi-tenant data platform, ingesting data from APIs, databases, and event sources.
- Build and maintain Data Platform APIs that allow teams to ingest, process, and access data easily and reliably.
- Implemented tenant-specific logic by following existing configuration and naming conventions.
- Apply tenant-level data isolation using schemas, partitions, or access controls.
- Build models from existing templates used for financial and operational reporting. Develop models for analytics and reporting, maintaining consistency with shared data models.
- Monitor scheduled pipelines, investigate failures, and resolve data quality issues and inconsistencies.
- Maintain daily and incremental data loads into the data warehouse.
- Assist with onboarding new clients by validating source data and testing pipeline outputs.
- Work closely with senior data engineers to learn patterns for multi-tenant data isolation.
- Collaborate with analytics, product, and customer facing teams to understand reporting needs
- Support strict regulatory and audit requirements by following data handling, retention, and audit guidelines.
- Handle financial and sensitive data (PII) according to company policies and regulatory standards (e.g. POPIA).
- Apply least-privilege access and role-based access controls, and support data protection through masking, encryption, and established security standards.
Technical Skills
- Programming languages - Good knowledge of programming languages such as Python, especially used for pipeline and data manipulation.
- SQL - working experience using SQL for data cleaning, aggregation, data transformation and integration.
- Data Warehouse - have a fundamental understanding of data warehousing solutions and platforms.
- Databases - hands-on experience working with relational and non-relational databases.
- Cloud computing - comfortable building data solutions using cloud-hosted services or data platforms.
- Data modelling and ETL - Can communicate and translate business requirements into existing data models.
- Data Pipeline Development - build and validate smaller-scale data pipelines independently.
- CI/CD and Version Control - apply best practices for managing pipelines and data workflows.