Sr. Business Intelligence Analyst

McKesson•Mississauga, ON

16d•Onsite

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. As a senior member of the Enterprise Portfolio Management Office (EPMO) within McKesson Technology (MT), this position plays a critical role in translating complex data into strategic insights that drive enterprise decision-making, portfolio optimization, and operational efficiency. The Sr. BI Analyst will lead data initiatives that enhance visibility, drive accountability, and support performance measurement across portfolios, programs, and IT investments. This role requires a high degree of technical expertise, cross-functional collaboration, and business acumen to influence outcomes at both tactical and strategic levels. You will champion data quality, standardization, and governance practices, working closely with stakeholders across MT, finance, and business units to design and deliver impactful analytical products and visualizations. This position will focus on designing and deploying automation solutions and scalable data products using tools such as Power Automate, Power Apps, Power BI, and Microsoft Fabric. You will collect, connect, and transform data from a variety of systems, building reusable workflows, apps, and self-service analytics that drive decision-making and operational efficiency. A key responsibility will be to establish and protect trusted data sources—ensuring they are well-governed, consistently structured, and easily accessible for business users. The role requires a strong understanding of automation, low-code/no-code platforms, and data modeling practices that support both operational reporting and proactive insights. You will work closely with internal teams to translate business needs into automated solutions, self-service dashboards, and predictive analytics. Responsibilities include designing user-friendly interfaces, developing automated data pipelines, enabling self-service capabilities, and supporting best practices in data quality, governance, and reusability.

Requirements

Degree or equivalent and typically requires 7+ years of relevant experience
Strong experience building automated analytics solutions in Power BI and/or Fabric
Hands-on experience designing workflow automations using Power Automate or similar tools
Solid SQL proficiency for transforming complex operational and financial data
Experience with modern data engineering platforms (Fabric, Databricks, or Snowflake)
Practical experience applying generative AI tools (e.g., Copilot, Azure, OpenAI) to business workflows
Experience with predictive analytics (e.g. correlational studies, regression analysis)
Experience working with executive leadership
Ability to translate business problems into decision intelligence solutions
Strong cross-functional partnership and product-thinking mindset

Nice To Haves

Familiarity with portfolio and project management platforms
Working knowledge of Python for data engineering and ML experimentation
Strong understanding of modern data architecture and governance principles
Exposure to MLOps or operationalizing machine learning workflows
Experience designing user-centric analytics or automated workflows

Responsibilities

Design, build, and operationalize automated workflows that reduce manual effort across portfolio lifecycles
Develop AI-assisted capabilities that enhance decision-making and governance
Build predictive and rules-based models that support prioritization, risk detection, and delivery forecasting
Engineer clean, reliable data pipelines needed for automation and AI models
Collaborate with IT, Finance, and EPMO leaders to translate business questions into scalable AI and automation solutions
Implement data quality and integrity practices that ensure AI and automation outputs remain reliable and auditable
Build reusable analytics assets that serve as the foundation for AI-enabled portfolio insights
Continuously assess emerging tools and capabilities to advance maturity of AI and automation