Lead Solution Architect, Customer Analytics, EDW & AI

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.

Job Title:LeadSolutionArchitect–CustomerAnalytics,EnterpriseDataWarehouse&AI

PositionSummary

TheLeadSolutionArchitect–CustomerAnalytics,EnterpriseDataWarehouse&AI is responsible for establishing enterprise-grade technical architecture that delivers sustained business value across system-wide, mission-critical programs. This role owns architectural components and ensuresalignmenttofuture-statetechnologyvision,directsfit-gapanalysis,validatesmigrationplans,andevaluatestechnologyplatformsandarchitecturalpatternstoensuresolutionsmeetrigoroussecurity,performance,reliability,compliance,andoperabilityexpectations.

This role will focus on customer-facing analytics, enterprise data warehouse integrations, reporting products, APIs, dashboards, semanticmodels,andAI-enableddataproducts.Thearchitectwillguidefull-stackengineeringandEDWteamstodesignscalable,secure,andreliableplatformsthatdeliveractionableinsightstocustomersthroughdashboards,APIs,semanticlayers,andintelligentAI-poweredexperiences.

The successful candidate will bringdeepexperienceindataanalytics,large-scaleEDWintegrations,cloud-nativearchitecture,softwaredelivery,andenterpriseAIsolutions,includingRetrieval-AugmentedGeneration,AgenticAIframeworks,LLMorchestration,vectorsearch,AIAPIs,andAzure-basedAIgovernance.

Operating with a high degree of autonomy, the Lead SolutionArchitectwillconsultacrossmultipledomains,harmonizeinitiativeswithenterprisearchitecture,setandenforcestandards,providecleartechnicalrecommendationstonon-technicalstakeholders,andadvancemeasurableoutcomesalignedwithMcKesson’sstrategicobjectives.

KeyResponsibilities

EnterpriseSolutionArchitecture

• Defineandownthetargetarchitectureforcustomeranalytics,enterprisedatawarehouseintegrations,reportingproducts,APIs,semanticmodels,dashboards,andAI-poweredinsights.

• EstablisharchitecturestandardsandreferenceimplementationsacrossSnowflake,Databricks,datamodeling,orchestration/ELT,APIs,front-endconsumption,andcustomer-facingAIcapabilities.

• Translatebusinessrequirementsintoscalablearchitecturedesignsthatalignwithenterprisearchitectureprinciples,businessobjectives,andtechnologystandards.

• Evaluatetechnologyoptions,platforms,andarchitecturalpatternstorecommendsecure,scalable,andcompliantsolutioncomponents.

• Leaddesignreviewsandprovidearchitecturaldirectionforhigh-impactinitiativesacrossdata,application,AI,andcloudplatforms.

• Ensuresolutionsmeetnon-functionalrequirementsforavailability,performance,security,observability,compliance,operability,andcostefficiency.

CustomerAnalytics,EDW&DataPlatformArchitecture

• LeadEDWintegrationarchitecturebydefiningresilientELT/ETLpatterns,datacontracts,lineage,qualitychecks,governancecontrols,andmeasurableserviceexpectations.

• Modeldataforanalyticsusingfacts,dimensions,semanticlayers,anddataproductsthatsupportBItools,APIs,reportingapplications,andAIconsumptionpatterns.

• Driveperformancetuning,partitioning,clustering,caching,andcostgovernanceacrossstorage,compute,andquerylayers.

• DesignarchitecturepatternsthatallowstructuredandunstructuredenterprisedatatobesecurelyconsumedbyAIsolutionsthroughgovernedRAGpipelines.

• Definemetadata,lineage,governance,andknowledge-managementstrategiestoimprovetrust,retrievalquality,andresponsegrounding.

• Architectsemanticlayers,dataproducts,andknowledgegraphsthatimprovecontextualretrievalandreasoningacrosscustomeranalyticsplatforms.

AI,RAG&AgenticAIArchitecture

• DefinearchitecturepatternsforAI-poweredanalyticsproducts,includingconversationalanalytics,naturallanguagequeryexperiences,automatedinsightgeneration,intelligentreporting,andautonomousworkfloworchestration.

• DesignscalableAgenticAIarchitecturesthatleverageLLMs,multi-agentorchestrationframeworks,toolcalling,memorymanagement,enterpriseAPIs,andsecureexecutionpatterns.

• Establish reference architecturesforRAGsolutions,includingdocumentingestion,chunkingstrategy,embeddinggeneration,vectorsearch,semanticretrieval,promptorchestration,grounding,andevaluationframeworks.

• LeadintegrationofenterprisedataproductswithAzureOpenAI,AzureAIFoundry,AzureAISearch,vectordatabases,andexternalAIAPIs.

• Define and promote AIgovernancepracticescoveringresponsibleAI,modelmonitoring,promptsafety,privacy,auditability,explainability,andriskmanagement.

• Establishbestpracticesforpromptengineering,modelevaluation,AIobservability,retrievalqualitymeasurement,agenttesting,andcontinuousmodelimprovement.

EngineeringLeadership&DeliveryEnablement

• Partnerwithfull-stackengineeringteamstoshapeserviceboundaries,APIcontracts,integrationpatterns,andsecuredataconsumptionmodels.

• GuideengineeringteamsinbuildingAIservices,copilots,intelligentagents,andconversationalexperiencesintegratedwithcustomer-facinganalyticsproducts.

• Createarchitecturedecisionrecords,solutiondiagrams,APIspecifications,datacontracts,standards,andknowledge-sharingartifacts.

• Mentorengineers,dataengineers,andarchitectsonarchitecturepatterns,securecoding,testing,reliability,logging,metrics,tracing,alerting,incidentresponse,andoperationalreadiness.

• Drivepracticalexecutionfromarchitecturedocumentstoworkingreferenceimplementationsandreusableproduction-gradepatterns.

• Partneracrossproduct,datagovernance,security,customersuccess,engineering,andbusinessstakeholderstotranslatebusinessoutcomesintotechnicalroadmaps.

Security,Compliance&Governance

• Embedsecuritybydesign,includingauthentication,authorization,leastprivilege,encryption,secretsmanagement,secureAPIs,andsecuredatasharing.

• DefinecontrolsforsecureenterprisedatauseinGenAIapplications,includingvectorstores,embeddings,prompts,LLMinteractions,modeloutputs,andauditability.

• SupportgovernanceforPII/PHI,regulatoryrequirements,securitycontrols,andauditreadiness.

• Leadarchitecturereviews,riskassessments,threatmodeling,andsecure-by-defaultdesignreviewsfordataandAIproducts.

• Ensuresolutionarchitecturedecisionsalignwithenterprisestandards,architectureguidelines,andgovernanceprinciples.

MinimumQualifications

• Bachelor’sdegreeinComputerScience,InformationSystems,Engineering,orarelatedfield,orequivalentexperience.

• Typically10+yearsofarchitecture/engineeringexperience,includingsustainedleadershipofenterprise-scale,cross-platformprograms.

• Experiencedesigning,governing,anddeliveringcustomer-facinganalytics,reporting,ordata-productplatforms.

• Hands-onexperiencewithlarge-scaleenterprisedatawarehouseintegrations,dataarchitecture,datamodeling,ELT/ETLpatterns,dataquality,lineage,governance,andprivacy.

• ExperiencewithSnowflake,Databricks,Spark,SQL,semanticmodels,dataproducts,andanalyticsplatforms.

• ExperiencewithmodernserviceandAPIdesign,includingREST/JSON,authentication,authorization,versioning,errorhandling,andsecureAPIconsumption.

• ExperiencedesigninganddeployingGenerativeAIsolutionsinenterpriseenvironments.

• DemonstratedexperiencewithRAGarchitectures,includingvectordatabases,embeddings,documentindexing,semanticsearch,retrievalorchestration,andpromptworkflows.

• PracticalexperiencewithAgenticAIsolutions,includingmulti-agentsystems,orchestrationframeworks,toolintegration,memorypatterns,reasoningworkflows,andautonomoustaskexecution.

• ExperiencewithAzureOpenAI,AzureAIFoundry,AzureAISearch,LLMAPIs,embeddingAPIs,vectordatabases,orrelatedAIservices.

• Strong understanding ofpromptengineering,modelevaluation,hallucinationmitigation,guardrails,ResponsibleAIcontrols,andAIapplicationobservability.

• Abilitytotranslatecomplexarchitecturedecisionsintoclearrecommendationsfortechnicalandnon-technicalstakeholders.

• Experiencealigningproduct,engineering,security,data,andoperationsteamstooperationalizetargetarchitecturesanddelivermeasurablebusinessoutcomes.

CoreCompetencies

• EnterpriseArchitectureLeadership:Setsarchitecturedirection,definesstandards,andguidesteamstowardsecure,scalable,andbusiness-alignedsolutions.

• SystemsThinking:Balancescustomerexperience,dataquality,security,scalability,performance,cost,compliance,andoperability.

• AIArchitecture&Governance:DesignsresponsibleAIecosystemsthatintegrateenterprisedata,analyticsplatforms,APIs,andintelligentagents.

• TechnicalInfluence:Buildsconsensusacrossproduct,engineering,data,security,operations,andexecutivestakeholders.

• PragmaticExecution:Movesfromarchitecturestrategytoreferenceimplementations,reusablepatterns,andproduction-readydelivery.

• Communication&Storytelling:Simplifiescomplextrade-offsandclearlycommunicatesrisks,options,andrecommendationstotechnicalandnon-technicalaudiences.

PreferredQualifications

• Experience integrating analytics with BI tools such as Power BI,GoogleLooker,semanticlayers,datacatalogs,andgovernancetooling.

• Experiencewithclouddataplatformsandservices,includingSnowflakeonAzure,Databricks,AzureDataFactory,objectstorage,andeventstreamingplatformssuchasKafka.

• ExperiencewithAzureAIFoundry,AzureOpenAI,AzureAISearch,MicrosoftFabricAIcapabilities,SemanticKernel,LangChain,LangGraph,AutoGen,CrewAI,orsimilarframeworks.

• ExperienceimplementingvectordatabasesandsemanticretrievalplatformssuchasAzureAISearch,Pinecone,Weaviate,Chroma,orequivalenttechnologies.

• Experiencebuildingconversationalanalytics,AIcopilots,knowledgeassistants,andintelligentworkflowautomationsolutions.

• ExperiencewithAIevaluationframeworks,retrievalqualitymetrics,groundingvalidation,prompttesting,safetyevaluation,andproductionmodelmonitoring.

• ExperiencedeployingAIapplicationsusingcontainerizedandcloud-nativearchitecturesonAzure.

• ExperienceinhealthcareIT,regulatedindustries,orotherlarge-scaleenterpriseenvironments.

Physical Requirements:General Office Demands

Relocation assistance / allowance is not budgeted 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 McKesson's 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, please click here.

Our Base Pay Range for this position

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McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit ourEqual Employment Opportunity page.

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