Data Analyst

Cardinal Health

4d•$80,900 - $115,500

About The Position

Medical Segment Sales Analytics delivers customer, sales, revenue, gross profit, pricing, and operational insights that enable informed strategy and execution. The Data Analyst, Data Analytics will work with customer, marketing, sales, distribution, and third-party data to convert complex data sets into clear, actionable insights through dashboards, reports, analyses, spreadsheets, and executive-ready presentations. We are seeking a highly analytical, business-oriented professional who is skilled in data extraction, transformation, validation, visualization, and storytelling. The ideal candidate will combine strong technical capabilities with sound business judgment, intellectual curiosity, and the ability to translate ambiguous business questions into meaningful analytical deliverables. The Data & Analytics function oversees the analytics lifecycle to identify, analyze, and communicate relevant insights that support business decisions, improve execution, and anticipate opportunities for competitive advantage. This role will contribute to the design, development, and delivery of business intelligence and analytics solutions, while helping ensure data accuracy, consistency, usability, and adoption across stakeholder groups.

Requirements

Bachelor’s degree in a related field or equivalent work experience.
5+ years of experience in data analytics, business intelligence, reporting, or related analytics function preferred.
Strong experience working with large, complex data sets and multiple data sources, including customer, sales, distribution, operational, and third-party data.
Hands-on experience with Google BigQuery, Databricks, relational databases, and SQL-based analysis; Oracle and SQL Server experience preferred.
Advanced experience developing dashboards, reports, and visualizations using tools such as Tableau and Looker, with strong understanding of visual design principles and effective information presentation.
Experience using data exploration, preparation, and mining tools such as Alteryx.
Ability to define analytical plans, develop hypotheses, analyze performance trends, and translate findings into practical business recommendations.
Demonstrated ability to convert ambiguous or evolving business requests into clear requirements, analytical approaches, and concrete deliverables.
Experience supporting business-critical applications, identifying issues, troubleshooting root causes, and partnering with technical teams to resolve data or reporting defects.
Experience with modernizing, migrating, or supporting legacy reporting and data environments into cloud-based analytical solutions.
Strong communication, presentation, and storytelling skills, with the ability to explain complex analysis clearly to both technical and non-technical audiences.
Ability to work effectively in a fast-paced, changing environment while managing priorities, deadlines, and stakeholder expectations.

Nice To Haves

Experience with Celonis or other process mining solutions.
Experience working in Agile delivery environments.
Understanding of data warehousing concepts, ETL/ELT processes, stored procedures, data ingestion patterns, and dimensional modeling.
Experience working with SAP or other enterprise source systems.
Working knowledge of Python and/or R for data analysis, automation, or statistical modeling.
Understanding project management lifecycle concepts and cross-functional delivery practices.
Exposure to AI-enabled analytics, prompt engineering, and emerging agentic AI frameworks to improve productivity and analytical outcomes.

Responsibilities

Bachelor’s degree in a related field or equivalent work experience.
5+ years of experience in data analytics, business intelligence, reporting, or related analytics function preferred.
Strong experience working with large, complex data sets and multiple data sources, including customer, sales, distribution, operational, and third-party data.
Hands-on experience with Google BigQuery, Databricks, relational databases, and SQL-based analysis; Oracle and SQL Server experience preferred.
Advanced experience developing dashboards, reports, and visualizations using tools such as Tableau and Looker, with strong understanding of visual design principles and effective information presentation.
Experience using data exploration, preparation, and mining tools such as Alteryx.
Ability to define analytical plans, develop hypotheses, analyze performance trends, and translate findings into practical business recommendations.
Demonstrated ability to convert ambiguous or evolving business requests into clear requirements, analytical approaches, and concrete deliverables.
Experience supporting business-critical applications, identifying issues, troubleshooting root causes, and partnering with technical teams to resolve data or reporting defects.
Experience with modernizing, migrating, or supporting legacy reporting and data environments into cloud-based analytical solutions.
Strong communication, presentation, and storytelling skills, with the ability to explain complex analysis clearly to both technical and non-technical audiences.
Ability to work effectively in a fast-paced, changing environment while managing priorities, deadlines, and stakeholder expectations.
Applies comprehensive knowledge of data analytics concepts, business processes, technical capabilities, and reporting practices to complete varied assignments and projects.
Works independently on complex assignments of moderate to large scope, receiving general guidance on new or highly complex work.
Develops practical, scalable, and well-documented analytical solutions that align with business objectives and organizational standards.
Partners with business stakeholders understand objectives, clarify requirements, and translate business needs into analytical and technical solutions.
Communicates insights, risks, assumptions, and recommendations clearly through dashboards, written summaries, and presentations.
Collaborates effectively with cross-functional teams, including business partners, technology teams, offshore resources, and peer analytics teams.
Contributes to process improvements, standards, documentation, and reusable analytical approaches that improve quality and efficiency.
Ensures work is reviewed against business objectives, quality expectations, data accuracy, and timely delivery.
May provide guidance or mentorship to less experienced colleagues and help promote analytics best practices across the team.