Intermediate Data Analyst

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.