Lead Solution Architect, Customer Analytics, EDW & AI

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

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

Operating with a high degree of autonomy, the Lead Solution Architectwillconsultacrossmultipledomains,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 architectures forRAGsolutions,includingdocumentingestion,chunkingstrategy,embeddinggeneration,vectorsearch,semanticretrieval,promptorchestration,grounding,andevaluationframeworks.

LeadintegrationofenterprisedataproductswithAzureOpenAI,AzureAIFoundry,AzureAISearch,vectordatabases,andexternalAIAPIs.

Define and promote AI governancepracticescoveringresponsibleAI,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 of promptengineering,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

$122,100 - $162,800

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