Data Engineer

We are X, bigly labs, Dis-Chem’s high-performance innovation hub; a place where bold ideas meet data, design, and radical customer focus to reimagine what healthcare can be.

Our mission is to power the future of healthcare by lowering costs, unlocking new possibilities, and improving access to healthcare for all South Africans. We do this through cutting-edge digital solutions that deliver smarter, more human, and truly patient-focused experiences. Here, your work is not limited to a whiteboard; it becomes real. It drives decisions, shapes experiences, and moves healthcare forward. We are driven by one big question: How do we use data and today’s technology to build breakthroughs to better health?

There’s only one question left: are you ready to make healthcare smarter, and actually mean it?

We are seeking a Senior Data E****ngineer to lead the development of a modern, scalable, and secure data platform that supports enterprise-wide analytics, machine learning, and AI initiatives. The Senior Data Engineer will be responsible for designing, building, maintaining and optimising robust data pipelines and enabling governed data sharing with external partners. This role will work closely with data analysts, data scientists, and AI engineers to ensure the scalable, secure, and high-performance data platforms that power analytics, AI, machine learning and operational excellence required by business teams. You will build data assets to provide robust, compliant and agile solutions to support in healthcare, retail, and insurance innovations. 

WHAT WE'RE LOOKING FOR?

Minimum 

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
• Certification in cloud platform: AWS, Azure Data Engineer (DP-203/DP-700), or Databricks Certified Data Engineer
• 6+ years of experience in data engineering or software development 
• 3+ years of hands-on experience with Databricks Intelligence Platform and implementing Medallion Architecture. 
• Strong proficiency in Python, SQL, Spark, and cloud-native data services (e.g., Azure Data Lake, AWS S3, GCP BigQuery)
• Familiarity with cloud-native data integration tools (e.g. SAP Datasphere, Snowflake Airflow)
• Experience in delivery and collaboration tools: GitHub, JIRA, Confluence and MIRO 
• Proven experience in developing data platforms that support data science, data analytics and AI workloads
• Extensive experience in ETL development and Data Pipelines with CI/CD, as well as data governance, and data quality frameworks
• Solid understanding of data science workflows, model lifecycle, and AI concepts