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?
The Intermediate Data Analyst turns business questions into evidence: analysis in Databricks SQL and statistics on certified gold, delivered as findings and recommendations stakeholders act on. The deliverable is a decision, not a dashboard. Power BI carries the recurring answers as source-of-truth dashboards on certified gold and metric views, thin windows with no logic in DAX and no modelling in the tool.
WHAT WE'RE LOOKING FOR?
Minimum
- Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science or a related field, or equivalent practical experience.
- 3 to 5 years in data analysis or business analytics.
- Strong SQL: joins, aggregations and window functions on large datasets.
- Working knowledge of statistics: distributions, hypothesis testing and significance.
- Data modelling literacy: reads and navigates star schemas and gold models, and mirrors them in Power BI semantic models without building logic in the tool.
- Power BI: builds dashboards with semantic-model wiring, DirectQuery on facts and Dual on dimensions, with clear layout and visual storytelling.
- Business understanding: frames analysis in the commercial mechanics of the domain, not just the data.
- Excel for working with data.
Advantageous
- Python or R for deeper statistical work.
- Databricks AI/BI dashboards.
- AI-assisted analysis: assistants for speed, every number verified against certified gold before it reaches a decision-maker.
- Report lifecycle and catalogue management.
- SAP business context: what BW reports mean and the data behind them. We teach this during the migration off SAP BW.
- Retail data, ideally pharmacy retail. Healthcare or financial services also count.
WHAT YOU WILL BE DOING?
- Analyse certified gold datasets in Databricks SQL, using statistics and hypothesis testing, so that conclusions are evidence rather than opinion.
- State findings and recommendations with the evidence behind them so that stakeholders can act.
- Build Power BI dashboards on certified gold and metric views by wiring semantic models that mirror gold, DirectQuery on facts, Dual on dimensions and no logic, so that every number matches the certified source.
- Turn business questions into testable analytical questions and present findings so that stakeholders understand what the data says and what to do about it.
- Use certified gold and metric views only, document methods and assumptions, and promote recurring metrics to Analytics Engineers for certification as metric views, so that analysis stays reproducible and consistent.
WHO YOU ARE?
- Have the business context behind the questions asked and the gold-layer contract.
- Be able to explain findings to technical and business
- Be able to partners with stakeholders from question
- Owns the accuracy and delivery of own analyses end to end.
- Manages own backlog and commitments; no people management.
Our values show up in how we think, build, and make choices that make an impact. We are building a culture that drives progress; one that fixes friction, chases what changes, and owns the outcome. We design with tomorrow in mind, ask sharper questions, and answer them with care, urgency, and systems that scale.
Think you’ve got energy, curiosity, and guts? Come hold the space, make it matter, and own a breakthrough.