Data Engineer Permanent•Johannesburg, Gauteng, ZA
Job Description
Our client is seeking an experienced Data Engineer to join their data and analytics environment. The successful candidate will be responsible for acquiring, integrating, transforming and managing data from multiple enterprise systems to create reliable, high-quality datasets that support business intelligence, analytics and data science initiatives.
Key Responsibilities
- Extract data from multiple source systems, including ERP, TMS, WMS, CRM, Finance, HR and external vendor platforms.
- Connect to databases, APIs, flat files, cloud platforms and third-party applications.
- Design, develop and maintain scalable ETL/ELT data pipelines.
- Integrate data from multiple sources into a centralised data platform.
- Use advanced SQL to cleanse, transform and enrich data.
- Standardise data definitions and resolve data inconsistencies and duplicates.
- Design and maintain fact and dimension tables.
- Build and optimise star and snowflake schemas.
- Develop and optimise SQL queries, joins, aggregations and calculations.
- Ensure data accuracy, completeness, consistency and reliability.
- Implement data validation and reconciliation controls.
- Deliver trusted datasets to Power BI and other reporting platforms.
- Support BI Analysts and Data Scientists with curated, business-ready datasets.
- Improve data availability, accessibility and usability across the organisation.
Qualifications
Degree in Computer Science, Information Systems, Data Engineering or related field.
Experience
- 3–5 years' experience in Data Engineering.
- Experience with Data Warehousing and Data Modelling.
- Experience integrating data from multiple source systems.
- Experience working with Power BI and analytical datasets.
- Proficiency in SQL and Python and/or R.
- Experience with Databricks, Snowflake and/or Azure would be advantageous.
- Experience with version-control tools such as Git.
Technical Knowledge
- Advanced SQL and database development.
- Data warehousing, dimensional modelling and data architecture.
- ETL/ELT development and data pipeline design.
- Python/R and data analytics.
- Machine learning concepts and feature engineering.
- Cloud environments, particularly Microsoft Azure and/or AWS.
- Enterprise and supply-chain systems such as ERP, WMS and TMS.
- Databricks and/or Snowflake.
- Strong analytical and problem-solving skills.
- Data modelling and statistical analysis.
- Data storytelling and BI enablement.
- Feature engineering and model development.
- Strong attention to detail and data quality focus.
- Ability to collaborate effectively with cross-functional teams.
- Strong business acumen and commercial awareness.
- Innovative and continuous-improvement mindset.
Ideal Candidate
The ideal candidate will be a technically strong Data Engineer with a relevant degree and 3–5 years' experience working with complex datasets, multiple source systems and modern data platforms. They should be able to bridge data engineering and business intelligence requirements while ensuring data is accurate, trusted and fit for business decision-making.