DESCRIPTION

The Business Intelligence Analyst is responsible for the preparation, analysis, and reporting of business intelligence data to support decision-making processes. This role involves gathering reporting requirements, performing data analysis, and providing recurring reports for key stakeholders. The position requires collaboration with senior BI analysts and leaders to ensure accuracy, timely delivery, and actionable insights.

Key Responsibilities:

• Gather reporting requirements from stakeholders and analyze data to create accurate, timely, and recurring reports.
• Perform data quality assurance and validate conclusions to ensure reliability and accuracy.
• Select appropriate analysis methods based on business needs to provide the most relevant insights.
• Extract data from operational systems and reporting databases to aid in decision-making.
• Use globally standardized dashboards and reporting practices to meet business intelligence needs.
• Collaborate with senior BI analysts and BI leaders to ensure clarity of reporting objectives and purposes.
• Ensure effective communication with stakeholders regarding analysis findings and reporting.
• Actively contribute to building and sustaining Cummins' leadership culture by demonstrating leadership behaviors.

• Minimum 4 years of experience in Data Analytics, with strong analytical and problem-solving skills.
• Proficiency in SQL and Power BI (Power Query, DAX); advanced Excel skills (VBA/Macros) required.
• Experience with Python, Power Apps, Power Automate, ETL processes, and data modeling.
• Experience working with big data, applying statistical concepts, and drawing clear, accurate conclusions.
• Preferably experience in sales or sales support roles.
• Experience in supporting global stakeholders and delivering data insights.

• Communicates effectively: Deliver clear, multi-mode communications that cater to the unique needs of different audiences.
• Nimble learning: Continuously learn through experimentation, using successes and failures as opportunities for growth.
• Self-development: Actively seek new challenges and development opportunities, both formal and informal.
• Tech savvy: Anticipate and adopt new digital technologies and innovations for business insights.
• Data Analytics: Analyze and communicate data, applying statistical concepts, data visualization, and problem-solving techniques to extract meaningful insights.
• Data Quality: Identify and correct data flaws to support effective information governance and decision-making.
• Values differences: Recognize and appreciate diverse perspectives and cultures.
• Action oriented: Embrace challenges and new opportunities with urgency, energy, and enthusiasm.
• Data Mining: Use data exploration and visualization techniques to identify relationships and patterns, facilitating sound conclusions for business decisions.

• Education: Bachelor's degree in Data Science, Economics, Computer Science, Statistics, or a relevant quantitative field, or equivalent experience.