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Sandton: SQL Data Engineer

Sandton: SQL Data Engineer

Posted on 2025-07-04 00:00:00

Job Summary

We are looking for a capable and detail-oriented SQL Developer / Data Engineer to design, build, maintain, and support high-quality data pipelines that empower insight-driven decision-making and efficient campaign execution. You will play a key role in ensuring the reliability, performance, and quality of data pipelines, with a strong emphasis on compliance and metadata governance. Key Responsibilities Maintain and support existing data pipelines, ensuring optimal performance and minimal downtime. Identify opportunities to optimise and refactor data pipelines for improved efficiency and scalability. Ensure data integrity, quality, and compliance with metadata governance and industry standards. Develop and deploy new data pipelines and transformations according to business needs. Follow agreed development lifecycle processes, including requirements gathering, testing, version control, and deployment. Maintain and document code repositories (e.g., Git) and ensure code is modular, reusable, and well-documented. Collaborate with campaign teams, data analysts, and other stakeholders to ensure data solutions meet business requirements. Minimum Qualifications and Experience 3 years of professional experience in Data Engineering , with a strong focus on SQL-based development. Proven experience in maintaining, troubleshooting, and enhancing data pipelines in a production environment. Experience working within structured development methodologies (Agile/Scrum/Kanban preferred). Preferred Exposure and Experience Exposure to maintaining and improving internal data processing workflows and operations. Familiarity with campaign management environments or customer data platforms is advantageous. Experience working with large datasets and optimising SQL queries for performance. Technical Skills and Competencies SQL (Strong proficiency is essential) Experience with ETL tools or data integration platforms (e.g., Ab Initio is a bonus) Understanding of data modelling principles and best practices Knowledge of data quality assurance methodologies Familiarity with metadata and governance frameworks Experience with version control systems (e.g., Git) Soft Skills and Attributes Strong analytical and problem-solving skills Attention to detail and a commitment to producing high-quality, reliable data outputs Excellent communication and collaboration skills Ability to work independently and proactively identify improvement areas

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