The Business Intelligence Analyst is responsible for transforming data into actionable insights that support strategic and operational decision-making. This role focuses on analyzing trends, identifying relationships between metrics, explaining why changes happen, and communicating insights through clear, compelling narratives. The role also supports forecasting and forward-looking analysis and may use Python based analysis and visualization when BI tools alone are insufficient. This role goes beyond reporting and dashboards, it is centered on correlation, causation, forecasting, and storytelling.

Responsibilities:

• Ensure compliance with relevant regulations while promoting organizational transparency
• Develop and maintain business dashboards and reports using Power BI or similar tools.
• Analyze trends, patterns, and relationships across business metrics
• Perform root-cause analysis on KPI movements and anomalies
• Build and maintain basic forecasting and projection models for key business metrics
• Support scenario analysis and forward-looking insights (best / expected / worst cases)
• Use Python-based analysis and plotting when deeper exploration or custom visualization is required
• Translate business questions into analytical frameworks and metrics.
• Partner with stakeholders (Product, Finance, Operations, Engineering) to provide decision-ready insights
• Contribute to KPI definitions, metric documentation, and governance
• Present insights clearly to non-technical audiences, including leadership
• Strong proficiency in SQL for analytical querying and data exploration
• Hands-on experience with BI tools such as PowerBI, including ( Building dashboards and reports - Working with semantic models and measures - Applying filters, drill-downs, and row-level security concepts )
• Solid understanding of analytical concepts, including ( Trend analysis - Forecasting and projections - Correlation vs causation - Variance and comparative analysis )
• Experience working with data warehouses (BigQuery preferred)
• Working knowledge of Python for analysis, including ( Data exploration and transformation (e.g. pandas) - Plotting and visualization (e.g. matplotlib, seaborn, or equivalent) - Using Python notebooks or scripts to support analysis)
• Familiarity with data validation techniques to ensure analysis accuracy