Azure Data Engineering & BI

• Build and manage ETL/ELT pipelines using Azure Data Factory.
• Develop scalable data transformations using Databricks / PySpark / SQL.
• Apply data warehousing principles (dimensional modeling, SCDs, partitioning).
• Design and optimize Power BI dashboards and semantic data models.
• Ensure robust data quality, lineage, and governance across Azure components.

Data Analysis & Insights

• Capture and gather data from multiple sources (digital, operational, transactional, external, or partner data).
• Analyze trends, patterns, anomalies, and performance indicators to identify risks and opportunities.
• Build narratives, insights, and recommendations for business stakeholders.
• Forecast outcomes and measure the effectiveness of initiatives, programs, or action plans.

Reporting & Visualization

• Design and deliver reports using tools such as Power BI, Excel and relevant analytics platforms.
• Prepare concise summaries for Business Reviews, performance reviews, and strategic discussions.
• Maintain dashboards and templates that support ongoing monitoring and decision-making.

Data Management & Quality

• Identify relevant data sources and maintain databases and data systems.
• Set up data collection routines and manage data extraction processes.
• Clean, validate, and organize datasets; troubleshoot data quality issues.

Stakeholder Collaboration

• Work closely with internal business partners to define analytical needs and KPIs.
• Follow up on stakeholder requests to ensure insights are understood and actionable.
• Participate in scoping, review, and presentation meetings.

Team Contribution & Continuous Improvement

• Support and guide other analysts within the team, act as a problem solver.
• Apply standard methods and contribute to improving analytical practices, tools, and processes.
• Stay updated on analytics, BI, Azure technologies, and digital/data trends.