Data Analyst - BI and Data Framework

Role: Data Analyst – BI & Data Framework

 

Role Summary

The Data Analyst will primarily focus on building and sustaining the data framework that supports enterprise BI and analytics, while also providing operational analytics and Power BI support. The role will work across functions to ensure data is consistent, reliable, and analytically ready.

 

Key Responsibilities

Data Framework & Foundations (Primary)

• Design, maintain, and enhance core datasets and data models and data lineage used for BI and operational reporting.
• Define and document metric logic, data definitions, and transformation rules.
• Support data quality checks, reconciliations, and issue triage to ensure reporting accuracy.
• Maintain data documentation such as datasets, logic notes, and dependencies.

Business Intelligence & Visualization

• Develop and enhance Power BI datasets, reports, and dashboards.
• Apply visualization best practices to ensure clarity and actionability of insights.
• Support ad hoc analysis and enhancements aligned to business priorities.

Operational Analytics Support

• Support routine operational reporting, refreshes, validations, and exception analysis.
• Respond to data and reporting requests while balancing speed with governance.

Cross Functional Collaboration

• Partner with Finance, Operations, Technology, and Governance teams to align on data usage and expectations.
• Translate business needs into analytical requirements and structured data solutions.
• Participate in discussions on data landscape evolution and optimization.

 

Required Skills & Experience

• Strong hands-on Experience in SQL and Azure-based data environments with expertise in enterprise data frameworks, integration, and governance
• Experience in data management, data analysis, BI, or analytics roles.
• Exposure in Power BI (datasets, visuals, Power Query; DAX)
• Strong understanding of data structures, data modelling concepts, and reporting pipelines.
• Ability to work in cross functional teams.
• Strong analytical thinking and attention to detail.

 

Preferred Attributes

• Foundation oriented mindset (interested in “how data works,” not just outputs)
• Comfortable navigating data ambiguity and dependencies
• Strong ownership mentality with a quality first approach
• Clear communicator across technical and non technical audiences