Lead Data Analyst

Senior Data Analyst – Job Description
What You’ll Do
As a Senior Data Analyst, you will be a key driver of data-informed decision-making across the organization. Your primary focus will be on designing impactful dashboards and analytical solutions using Power BI, while working with cross-functional teams to translate business needs into scalable insights.

• Collaborate with Stakeholders: Understand business objectives, define KPIs, and translate requirements into data models and reports.
• Design in Power BI: Build high-quality, performant dashboards primarily using Power BI, with advanced DAX calculations and intuitive user experiences.
• Data Modeling: Create and optimize semantic models to support self-service reporting and accurate business logic.
• Insight Generation: Deliver ad hoc and recurring insights, visualizations, and presentations that tell a clear and actionable story.
• Data Quality & Governance: Ensure data accuracy and reliability, following best practices in data validation and report refresh design.
• Documentation & Support: Create detailed documentation and provide training to promote user adoption and data literacy.
• Project Management: Lead BI/reporting projects from ideation to deployment, ensuring stakeholder alignment and solution scalability.

Must-Haves

• 5- 7 years of experience in data analysis, business intelligence, or similar roles.
• Deep, hands-on experience with Power BI, including DAX for calculated measures and data modeling.
• Strong SQL skills for working with large datasets.
• Familiarity with Python or a scripting language for automation or data prep tasks.
• Strong communication skills for translating data findings into business-relevant insights.
• Proven ability to manage multiple projects in a dynamic, fast-paced environment.

Preferred Qualifications

• Hands-on experience with Databricks (e.g., Spark, Delta Lake) for data transformation or integration into BI workflows.
• Experience with other BI tools like Tableau or Cognos (secondary to Power BI).
• Familiarity with semantic modeling techniques (e.g., star/snowflake schemas).
• Understanding of data governance, data quality assurance, or master data management.
• Knowledge of UX/UI best practices in dashboard design for usability and performance.
• Exposure to version control systems (e.g., Git) for managing SQL or BI assets.

Graduation

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