Key Responsibilities

• Lead exploratory and advanced data analysis
• Design complex dashboards, KPIs, and analytical models
• Translating business problems into analytical approaches
• Mentor P1 and P2 data analysts
• Partner with data engineering and governance teams
• Promote analytics standards and best practices
• Discuss and report data analysis results and findings to different levels of stakeholders

Scope & Complexity

• Works with large, multi-source, or complex datasets
• Supports strategic and high-impact decisions
• Influences analytics direction and standards

Required Experience & Skills

• 5–8+ years of Data Analyst experience
• Expertise in using Business Intelligence tools such as PowerBI and Tableau
• Hands-on experience with Databricks, including notebooks, workflows, Delta Lake, and data pipelines.
• Strong proficiency in SQL and Python for data transformation, automation, and analytics.
• Experience designing and optimizing ETL/ELT processes in cloud-based data environments.
• Knowledge of data modeling, data governance, data quality, and metadata management principles.
• Experience working with large-scale structured and unstructured datasets.
• Strong analytical, problem-solving, and stakeholder communication skills.
• Intermediate to Advanced Data Analytics (Descriptive, Diagnostic Analysis, Predictive and Prescriptive Analysis)
• Strong data storytelling skills
• Basic project management and stakeholder management skills

Preferred Qualifications

• Databricks certifications (Databricks Fundamentals, Associate Data Engineer, Data Analyst, or equivalent).
• Experience with Lakehouse architecture, Medallion (Bronze, Silver, Gold) data models, and Delta Lake.
• Experience with Databricks Lakeflow, AI/BI, or data orchestration tools.
• Knowledge of Unity Catalog and enterprise data governance frameworks.
• Experience with cloud platforms such as Google Cloud Platform (GCP), Azure, or AWS.
• Experience integrating Databricks with reporting and visualization tools such as Tableau, Power BI, Looker, or Business Objects.
• Familiarity with AI, machine learning, or advanced analytics use cases.

Key Competencies

• Data Engineering & Data Management
• Cloud Data Platforms
• Data Governance & Quality Management
• Performance Optimization
• Business Intelligence & Analytics
• Automation & Process Improvement
• Cross-functional Collaboration
• Agile Delivery & Continuous Improvement

Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.

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