Senior Business Intelligence & Automation Analyst

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 tomorrows health today we want to hear from you.

The Senior Business Intelligence Analyst is a highly visible hands-on individual contributor responsible for building and scaling AIM28s analytics reporting and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead this role will design and own end-to-end data models ETL pipelines dashboards and automation solutions that transform complex fragmented data into trusted insights for executives and program addition this role will support other strategic projects as required.

The ideal candidate combines deep technical expertise in SQL data modeling BI visualization automation and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team this person will create the programs single source of truth for KPI benefit investment and value-realization reporting while driving self-service analytics reporting automation and AI-powered insights across the AIM28 portfolio.

The Senior Business Intelligence Analyst will lead the development of business intelligence data visualization analytics and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKessons AI-enabled transformation program organized around a portfolio of Big Bets each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it some lives in manual files and some is already visualized in dashboards the business teams built for themselves.

You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents so stakeholders can self-serve and get to insight faster. Where data is raw you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency strong knowledge of data design and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers.

This role works under the direction of the AIM28 Finance Lead partnering with Big Bet teams the transformation office and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program.

This is a pure individual-contributor role embedded in Finance not a role inside a BI or data engineering organization. There is no bench of other BIEs analytics engineers or data engineers to hand design build or troubleshooting off to you own the full stack yourself end to end. Because the role sits in Finance rather than Technology you should also be comfortable working fluently in financial concepts: ROI forecasting variance-to-plan and business-case logic gained through direct experience partnering with a business finance or FP&A team.

• Design build and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs benefits investments milestones and value realization. These dashboards are the single source of truth for program performance.

• Develop executive-facing reporting for monthly Steering Committee meetings business reviews and leadership updates. Translate complex program data into insights leaders can act on.

• Automate recurring benefit and program reporting end to end. Replace manual file-based processes with scheduled data flows that are validated and monitored.

• Find and implement automation opportunities across reporting workflows including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them.

• Build and maintain scalable ETL/ELT pipelines that extract transform and clean large multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting.

• Ingest and integrate data from Big Bet teams into harmonized consumable datasets and data models. Sources include raw operational data manually maintained files and dashboards the business built for itself.

• Establish the business logic that converts raw source data into certified reporting. Document the logic lineage and metric definitions well enough that someone else could audit or maintain the work.

• Design semantic models and curated datasets that people consume today through dashboards and self-service and that AI agents can consume over time.

• Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models so measurement stays consistent across Big Bets.

• Develop and monitor the KPIs that drive business decisions. Implement data-quality checks reconciliation and anomaly detection to protect trust in the numbers.

• Conduct deep-dive analyses of KPI movements benefit variances and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership.

• Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree triangulate across them to validate data fidelity.

• Enable governed self-service analytics for program and Big Bet stakeholders so fewer questions turn into ad hoc requests or one-off analyses.

• Own delivery end to end from requirements and solution design through build UAT and adoption. Work with business stakeholders data engineering and IT to keep solutions compliant with enterprise data standards.

• Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it.

• Set the standard for analytics practice (data integrity documentation versioning) across Big Bet teams and coach business analysts who build their own reporting.

• A builders mindset. You take loosely defined problems work out the business intent behind them and deliver working solutions end to end: requirements data model pipeline dashboard adoption.

• Comfort with ambiguity and imperfect data. Raw extracts manual spreadsheets inconsistent definitions and shifting requirements are the starting point here not a blocker.

• Business acumen and financial literacy. You understand core finance concepts ROI forecasting variance-to-plan business-case logic well enough to hold your own in a finance conversation not just translate what finance tells you. You have worked directly with a finance or FP&A team before and you can sit with finance and business partners understand benefit logic and business cases and translate between data and business needs.

• Comfort as a standalone technical IC. This role sits in Finance not in a BI or data engineering organization. There is no dedicated BIE team data engineering bench or technical manager to lean on for design review code review or troubleshooting you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end.

• A KPI and automation track record. You have developed and monitored KPIs that drive business decisions and you have built automated reporting systems that replaced manual processes.

• Executive presence. You have experience communicating and presenting analytical results to senior leadership in writing and in person.

• Ownership and judgment. You validate your own outputs make pragmatic build-versus-reuse trade-offs and earn trust by being right about the numbers.

• Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip.

• Curiosity about AI. You are interested in applying GenAI and agents to reporting and ideally you have already experimented with them.

• Expert SQL: complex query development window functions and performance tuning on large multi-dimensional datasets from multiple sources. You write queries that need little post-processing.

• Data modeling and design: dimensional and star-schema modeling semantic model design and harmonized dataset construction. You can evaluate an end-to-end data design for its strengths and weaknesses.

• BI and visualization: advanced Power BI and Tableau including data modeling DAX executive-grade dashboards and workspace and access management.

• ETL/ELT and pipelines: hands-on experience programming to extract transform and clean large datasets and building scheduled monitored pipelines in tools such as Databricks Microsoft Fabric Azure Data Factory or Snowflake.

• Scripting for automation: proficiency in Python or a similar language for data transformation and automation.

• Workflow automation: Power Automate Power Apps or comparable low-code tooling for reporting workflows. Exposure to modernizing legacy RPA into AI-enabled solutions is a plus.

• Analytics foundations: descriptive statistics trend and variance analysis and metric calibration plus enough familiarity with inferential methods to know when to use them.

• AI-enabled analytics (differentiator): applying LLM and GenAI capabilities to BI: automated narrative generation conversational analytics and agent-ready semantic layers.

• Executive tooling: advanced Excel and PowerPoint for analysis and executive storytelling.

Degree or equivalent and typically requires 7 years of relevant experience. Fewer years required if candidate holds a relevant Masters qualification.

Education

Bachelors degree in Computer Science Engineering Mathematics Statistics Economics Information Systems or a related quantitative field or equivalent experience. Advanced degree preferred.

• 7 years of experience as a Business Intelligence Engineer Data Analyst Analytics Engineer Data Engineer or a related occupation delivering BI analytics and reporting solutions.

• Deep SQL proficiency and strong knowledge of data design and data modeling.

• Expert-level dashboard development in Power BI (or equivalent) for executive audiences.

• Experience programming to extract transform and clean large datasets from multiple disparate sources including raw and manually maintained data.

• Experience designing and implementing custom automated reporting systems using automation and scripting tools such as Python and Power Automate.

• Track record of developing and monitoring KPIs to drive business decisions ideally including benefit or value-realization tracking for strategic programs.

• Demonstrated ability to establish business logic and metric definitions that turn raw data into trusted consumable reporting.

• Experience communicating and presenting analytical results to senior leadership.

• Strong analytical skills with the ability to translate data into actionable insights.

• Demonstrated organizational and prioritization abilities.

• Ability to navigate ambiguity and deliver independently in a fast-paced transformation environment.

• Working knowledge of core finance concepts (ROI forecasting variance-to-plan business-case and P&L mechanics) and direct experience partnering with a finance or FP&A team to translate financial methodology into data logic.

• Demonstrated ability to operate as the sole technical IC on a team without a dedicated BI or data engineering organization to lean on for support review or troubleshooting.

• Experience supporting large-scale transformation programs PMO or value-realization analytics or benefit tracking for strategic initiatives.

• Hands-on experience with Databricks Microsoft Fabric Azure data services or Snowflake.

• Experience embedding GenAI or AI-agent capabilities into analytics solutions such as automated narratives conversational BI or semantic layers for agents.

• Exposure to SAP/ERP data and enterprise source systems including S/4HANA migration environments.

• Experience with the theory and practice of design of experiments and statistical analysis of results.

• Experience enabling governed self-service analytics and establishing data and reporting SLAs.

• Healthcare pharmaceutical distribution or other regulated-industry experience is a plus.

• Agile delivery experience and strong documentation habits.

• PowerPoint creation and executive storytelling.

This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities.

McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role.

Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g. H1B O1 E3 H1B1 TN F1 OPT F1 STEM OPT F1 CPT etc.) now or in the future.

If you will require McKesson to provide immigration support or sponsorship now or in the future you should not apply for this position.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors including performance experience and skills equity regular job market evaluations and geographical markets. The pay range shown below is aligned with McKessons pay philosophy and pay will always be compliant with any applicable regulations. In addition to base pay other compensation such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson pleaseclick here.

Our Base Pay Range for this position

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