Job Purpose The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users. As a Data Engineer at Pepkor Lifestyle, you will play a critical role in the development and maintenance of our data infrastructure. You will work closely with cross-functional teams to ensure data availability, quality, and accessibility for analysis. The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users. Position outputs/competencies Collaborate with data scientists, analysts, and business stakeholders to understand data requirements. Design, develop, and maintain data pipelines and ETL processes. Implement and maintain data warehousing and data storage solutions. Optimize data pipelines for performance, scalability, and reliability. Ensure data quality and integrity through data validation and cleansing processes. Monitor and troubleshoot data infrastructure issues. Stay current with emerging technologies and best practices in data engineering. Systematic solution design of the ETL and data pipeline inline with business user specifications Develop and implement ETL pipelines aligned to the approved solution design Ensure data governance and data quality assurance standards are upheld Deal with customers in a customer centric manner Effective Self-Management and Team work Minimum qualification and Experience Bachelor's degree in Computer Science, Information Technology, or a related field. Proven experience as a Data Engineer in a professional setting. Proficiency in data engineering technologies and programming languages (e.g., SQL, Python, Scala, Java). Strong knowledge of data storage, database design, and data modelling concepts Experience with ETL tools, data integration, and data pipeline orchestration. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift). Excellent problem-solving and troubleshooting skills. Strong communication and collaboration skills. 5-10 years Experience and understanding in designing and developing data warehouses according to the Kimball methodology. Adept at design and development of ETL processes. SQL development experience, preferably SAS data studio and AWS experience The ability to ingest/output CSV, JSON and other flat file types and any related data sources. Proficient in Python or R or willingness to learn. Experience within Retail, Financial Services and Logistics environments. Redshift Technologies Understanding of data security and compliance best practices. Relevant certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer).
