Azure Data Engineering & BI
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Build and manage ETL/ELT pipelines using Azure Data Factory.
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Develop scalable data transformations using Databricks / PySpark / SQL.
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Apply data warehousing principles (dimensional modeling, SCDs, partitioning).
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Design and optimize Power BI dashboards and semantic data models.
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Ensure robust data quality, lineage, and governance across Azure components.
Data Analysis & Insights
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Capture and gather data from multiple sources (digital, operational, transactional, external, or partner data).
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Analyze trends, patterns, anomalies, and performance indicators to identify risks and opportunities.
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Build narratives, insights, and recommendations for business stakeholders.
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Forecast outcomes and measure the effectiveness of initiatives, programs, or action plans.
Reporting & Visualization
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Design and deliver reports using tools such as Power BI, Excel and relevant analytics platforms.
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Prepare concise summaries for Business Reviews, performance reviews, and strategic discussions.
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Maintain dashboards and templates that support ongoing monitoring and decision-making.
Data Management & Quality
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Identify relevant data sources and maintain databases and data systems.
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Set up data collection routines and manage data extraction processes.
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Clean, validate, and organize datasets; troubleshoot data quality issues.
Stakeholder Collaboration
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Work closely with internal business partners to define analytical needs and KPIs.
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Follow up on stakeholder requests to ensure insights are understood and actionable.
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Participate in scoping, review, and presentation meetings.
Team Contribution & Continuous Improvement
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Support and guide other analysts within the team, act as a problem solver.
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Apply standard methods and contribute to improving analytical practices, tools, and processes.
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Stay updated on analytics, BI, Azure technologies, and digital/data trends.