Data Analyst

Cardinal Health•Dublin, OH

1d•Hybrid

About The Position

The Data Analytics Function oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Analytics applies business process knowledge and data analytics to develop, recommend and communicate timely, accurate, relevant and actionable insights to support business decisions and objectives. The Business Insights Analyst supports strategic and operational decision‑making by executing analyses, building dashboards, and conducting data profiling with a focus on Inventory Management and Supply Chain. The role documents data lineage validates data quality, and partners with product, engineering, and business stakeholders to translate requirements into reliable datasets, reports, and insights. The Analyst contributes within agile teams to deliver enhancements, KPIs, and report improvements that strengthen business performance.

Requirements

Bachelor's degree in related field, or equivalent work experience, preferred
4-8 years of experience, preferred
Hands on analytical tool skills preferred
Experience developing creative and innovative analytical insights with high business value preferred
Strong communication skills preferred
Experience supporting supply chain, purchasing, or transportation teams preferred

Responsibilities

Execute data extraction and transformation using SQL, Python, or R.
Profile datasets to assess completeness, accuracy, and lineage; document key attributes and business rules.
Perform data validation, reconciliation, and user acceptance testing (UAT) for analytics and reporting.
Support predictive modeling efforts through feature preparation and exploratory analysis.
Build and maintain dashboards in Tableau or similar tools; ensure consistency and usability.
Translate complex data into clear, actionable insights and concise summaries for stakeholders.
Translate business needs into user stories and analytical requirements within agile teams.
Participate in sprint ceremonies and backlog refinement; provide timely status updates and risk flags.
Ensure alignment of analytical work with sprint goals, data quality standards, and product priorities.
Partner with data engineers, product owners, and business stakeholders to improve data pipelines and reporting.
Contribute to team documentation, templates, and best practices.
Seek opportunities to automate repeatable analyses and enhance data quality.