DATA ENGINEER

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.

Core Cloud Data Technology, CI/CD and Programming tools