Senior Business Intelligence Analyst

McKesson•Irving, TX

2d•$114,200 - $190,400•Hybrid

About The Position

The Senior Data Analyst serves as a strategic analytics partner within Shared Services & Business Solutions (SSBS), supporting enterprise initiatives through the development of scalable reporting, dashboards, data models, and analytical solutions. This role partners directly with internal customers, Revenue Operations Managers, business leaders, and cross-functional stakeholders to understand business challenges, define analytical approaches, and deliver insights that improve operational performance and decision-making. The Senior Data Analyst translates business requirements into actionable analytics solutions while ensuring data quality, reporting integrity, and sustainable delivery practices. Success in this role requires a combination of technical expertise, business acumen, consultative problem-solving, and the ability to transform complex data into meaningful insights that drive measurable business outcomes.

Requirements

Degree and typically requires 7+ years of relevant experience.
4-year College Degree, some Computer Science or Computer Programming coursework a plus
Proven track record applying analytics to drive business results and deliver insights
Advanced SQL expertise and experience working with large, complex datasets.
Strong Power BI and/or Tableau development experience, including dashboard design, data visualization best practices, and performance optimization.
Knowledge of data modeling, ETL processes, dimensional modeling, and data warehouse concepts.
Experience translating business requirements into reporting solutions, dashboards, and analytical products.
Experience developing scalable, reusable analytics solutions and self-service reporting capabilities.
Experience partnering directly with stakeholders to understand business needs and deliver data-driven solutions.
Strong problem-solving, analytical thinking, and root-cause analysis skills.
Ability to balance multiple priorities and deliver high-quality solutions in a fast-paced environment.
Excellent communication and data storytelling skills, including the ability to present findings and recommendations to both technical and non-technical audiences.
Proficient in Microsoft 365 applications, including Excel and PowerPoint.
Experience supporting healthcare, distribution, commercial operations, sales operations, shared services, or business services organizations.

Nice To Haves

MBA preferred
Experience with Databricks, Microsoft Fabric, cloud-based data platforms, and modern data architectures.
Experience with Python, advanced analytics, machine learning, predictive modeling, or automation technologies.
Experience leveraging Generative AI, Copilot, AI-assisted development tools, or intelligent automation to improve analytics delivery and business insights.
Knowledge of AI governance, responsible AI practices, and emerging analytics technologies.
Familiarity with Salesforce and enterprise reporting environments.
Demonstrated strategic thinking and independent problem-solving abilities.
Knowledge of the healthcare industry preferred.

Responsibilities

Design, develop, and maintain dashboards, reports, scorecards, and self-service analytics solutions using Power BI, Tableau, SQL, and related technologies to support operational performance and business decision-making.
Partner directly with internal customers, Revenue Operations Managers, and business stakeholders to understand business objectives, operational challenges, reporting requirements, and success measures.
Translate business requirements into scalable analytics solutions, including data models, reporting logic, visualizations, KPIs, and automated reporting capabilities.
Analyze complex datasets to identify trends, opportunities, risks, and performance drivers, delivering actionable insights and recommendations that support strategic and operational decisions.
Ensure data quality, accuracy, and reliability through data validation, governance practices, documentation standards, and ongoing maintenance of reporting assets.
Collaborate with enterprise data, technology, and architecture teams to enhance data accessibility, reporting capabilities, and analytics solution performance.
Drive continuous improvement through automation, innovation, and best practices, leveraging emerging analytics tools and technologies to improve efficiency, scalability, and business value.