IT - Principal Consultant | Architecture | Architecture - ALL

POC: Bharath Subramanya******ATTENTION ALL SUPPLIERS******READ BEFORE SUBMITTING: UPDATED CONTACT NUMBER and EMAIL ID is a MANDATORY REQUEST from our client for all the submissions Limited to 2 submission per supplier. Please submit your best. We prioritize endorsing those with complete and accurate information Avoid submitting duplicate profiles. We will Reject/Disqualify immediately. Make sure that candidate's interview schedules are updated. Please inform the candidate to keep their lines open.MANDATORY: Please include in the resume the candidate s complete & updated contact information (Phone number, Email address and Skype ID) as well as a set of 5 interview timeslots over a 72-hour period after submitting the profile when the hiring managers could potentially reach to them. PROFILES WITHOUT THE REQUIRED DETAILS and TIME SLOTS will be REJECTED.Job title: Databricks Technical ArchitectWork Location: Irving, TX - 75039Vendor Rate: $120 USD/hourMinimum years of experience: 10 yearsWould you require the candidates to meet you for in person interview? NoIs Skype/WebEx interview,OK? YesIs this onsite/remote position: HybridIf onsite, will you be considering relocation candidates: YesDoes this position require Visa independent candidates only? YesJob Description:Databricks Technical ArchitectWe are seeking a Databricks Architect to lead the data and analytics architecture supporting Finance processes across the enterprise.This role will bridge Finance business processes, SAP/ERP data, Databricks, enterprise data architecture, and AI/analytics. The architect will work closely with Finance process owners, data engineers, integration architects, enterprise architects, and technology teams to define and implement a scalable data foundation for Financial Shared Services.The ideal candidate combines strong Databricks and modern data platform expertise with a solid understanding of Finance processes, SAP financial data, data governance, and enterprise integration.Key ResponsibilitiesFinancial Shared Services Data StrategyPartner with Finance Shared Services leadership and process owners to understand business processes, pain points, KPIs, and data requirements.Translate Finance business requirements into comprehensive data architecture and roadmap.Define data products and analytical capabilities supporting areas such as:Accounts PayableAccounts ReceivableGeneral LedgerRecord-to-ReportProcure-to-PayOrder-to-CashFixed AssetsIntercompany AccountingCash ManagementFinancial CloseWorking CapitalIdentify opportunities to use data, analytics, automation, and AI to improve Finance Shared Services efficiency and decision-making.Databricks ArchitectureDefine and lead the implementation of scalable Databricks Lakehouse architecture supporting Finance data and analytics.Establish architecture patterns for ingestion, transformation, storage, data products, semantic models, and consumption.Design Bronze/Silver/Gold data layers and establish standards for financial data processing.Define approaches for batch and near-real-time data processing.Establish reusable patterns for data quality, lineage, metadata, security, and governance.Optimize Databricks workloads for scalability, performance, reliability, and cost.SAP and Enterprise Data IntegrationArchitect integration of SAP ECC and other enterprise applications with Databricks.Understand SAP Finance data structures, including financial accounting, controlling, procurement, assets, and related master data.Define authoritative sources and data ownership for financial information.Work with integration teams to establish appropriate patterns using APIs, events, replication, files, and other integration mechanisms.Ensure financial data remains consistent across SAP, Databricks, reporting platforms, and downstream applications.Data Products & AnalyticsLead the creation of governed Finance data products that can support reporting, analytics, forecasting, automation, and AI use cases.Define business and technical metadata for critical financial data.Establish common definitions for Finance KPIs and metrics.Enable self-service analytics while maintaining appropriate governance and controls.Support development of advanced analytics and AI capabilities using trusted financial data.Data Governance & ControlsEstablish data governance standards appropriate for financial data.Define data ownership, stewardship, lineage, quality rules, retention, and access controls.Ensure architecture supports financial controls, auditability, traceability, and regulatory requirements.Implement appropriate security and access models for sensitive financial information.Partner with Finance data owners to establish data quality and reconciliation processes.Architecture LeadershipServe as the primary technical architecture lead for Finance Shared Services data initiatives.Develop target-state architecture, solution architecture, integration patterns, and technical roadmaps.Review solution designs and ensure adherence to enterprise architecture standards.Guide engineering teams and provide technical leadership throughout implementation.Evaluate new Databricks, cloud, AI, and data technologies for applicability to Finance.Drive architecture decisions across business, data, application, integration, and technology domains.Required QualificationsBachelor's degree in Computer Science, Information Systems, Engineering, Finance, or a related field.8+ years of experience in data architecture, data engineering, enterprise architecture, or related technology roles.Strong hands-on architecture experience with Databricks and modern cloud data platforms.Strong understanding of Lakehouse architecture, Delta Lake, Spark, SQL, and data engineering patterns.Experience designing enterprise-scale data platforms and data products.Strong understanding of SAP data, preferably SAP S/4HANA Finance.Experience integrating SAP and non-SAP enterprise applications with modern data platforms.Strong understanding of data governance, security, metadata, lineage, and data quality.Experience working directly with Finance or Financial Shared Services organizations.Ability to translate complex business requirements into scalable technical architecture.Preferred QualificationsDatabricks certifications such as Databricks Certified Data Engineer or Data Architect.Experience with SAP Finance ProcessesExperience with SAP data replication or integration technologies.Experience with Azure, AWS, or GCP.Experience with enterprise event-driven architecture and APIs.Experience with Power BI or other enterprise analytics platforms.Experience implementing AI/ML or GenAI solutions using enterprise data.Experience with data mesh, data products, or domain-oriented data architecture.Experience supporting financial close, reconciliation, controls, and audit requirements.Experience working in large global enterprises with complex Finance organizations.Key CompetenciesFinance Process UnderstandingDatabricks & Lakehouse ArchitectureSAP Finance DataEnterprise Data ArchitectureData GovernanceCloud & Integration ArchitectureData Products & AnalyticsAI/ML & GenAI EnablementStakeholder ManagementArchitecture LeadershipSuccess MeasuresSuccess in this role will be measured by the ability to:Establish a scalable and governed Finance data foundation on Databricks.Reduce complexity and duplication across Finance data sources.Create trusted, reusable Finance data products.Improve data quality, reconciliation, and transparency across Financial Shared Services.Enable faster delivery of Finance analytics, automation, and AI use cases.Establish clear ownership and governance of critical financial data.Successfully translate Finance business priorities into an executable technology roadmap.Deliver measurable improvements in Finance Shared Services efficiency and decision-making.Role ProfileThis is a architecture leadership role requiring an individual who can operate comfortably at the intersection of Finance, SAP, Databricks, enterprise architecture, data engineering, and AI.The successful candidate should be able to move from What Finance process are we trying to improve? What data is required? Where does that data originate? How should it be integrated and governed? How should it be modeled in Databricks? What analytics/automation/AI capability can we enable? The role is therefore suited to a senior/principal-level Data Architect or Databricks Architect rather than a purely hands-on Databricks engineer.

Project Code: McKesson Corporation