Senior Data Analyst

About the Role:

We are looking for a Senior Data Analyst to join the BEES Fintech Data Analytics team. This role sits at the intersection of Business Intelligence, Advanced Analytics, and Analytics Engineering, transforming complex data into actionable insights that drive strategic decisions across Credit, Payments and Product teams.

The ideal candidate is not only able to build reports and dashboards but also understands statistical methods, experimental design, data modeling, and modern data platform concepts. This person acts as a trusted business partner, helping stakeholders identify opportunities, validate hypotheses, and make data-driven decisions.

What you'll do:

• Develop scalable analytical solutions using Power BI, Azure Databricks, SQL, and Python.
• Design and maintain dashboards, KPI frameworks, semantic models, and self-service analytics solutions.
• Transform data into actionable insights that support strategic business decisions.
• Apply statistical and analytical techniques to identify trends, opportunities, and business impacts.
• Perform exploratory analysis, ad hoc studies, and support experimentation initiatives.
• Partner with Product, Commercial and Technology teams to solve business problems through data.
• Ensure data quality, consistency, governance, and reliability across analytical products.
• Follow software engineering best practices, including Git-based development, version control, testing, and CI/CD processes.
• Communicate insights through effective data storytelling, visualizations, and executive presentations.

What you'll need:

• Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.
• Proven experience in Data Analytics, Business Intelligence, or related fields.
• Advanced SQL skills for data extraction, transformation, and analysis.
• Strong Power BI expertise, including dashboard development, DAX, data modeling, visualization best practices, and user experience design.
• Experience with Azure Databricks, SparkSQL, PySpark, and modern cloud-based analytics platforms.
• Proficiency in Python for data analysis and analytical solution development.
• Experience with Git, version control workflows, and CI/CD practices.
• Understanding of statistics, experimentation, hypothesis testing, and analytical problem-solving.
• Strong communication, stakeholder management, and data storytelling skills.
• Fluent English (written and spoken). Spanish is a plus.