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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager of the Enterprise Data Warehouse (EDW - **Company:** CareerCircle - **Location:** Irving, TX, United States - **Experience:** Expert - **Salary:** $118,100.0 - $196,900.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Artificial Intelligence, Data Analysis, Business Logic, Microsoft Azure, Business Intelligence Development, Code Generation, Data Architecture, Information Engineering, Data Governance, Data Warehousing, DevOps, Event-Driven Programming, Python (Programming Language), Machine Learning, SAP (Applications), Scala (Programming Language), SQL Databases, System Testing, Enterprise Data Management, Synapse Citrix, Data Processing, Data Ingestion, Azure Data Factory, Snowflake, Data Representation, Data Strategy, Data Lakes, Information Technology, Cosmos DB, Data Management, Looker Analytics, Data Pipelines, Databricks, Programming Languages - **Published:** June 5, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/tx/irving/9f9cf026-b802-4ca1-90a4-630c0b5bda3c ## About the Role Coaching Leadership Management Governance Innovation Scalability Data Quality Communication Prioritization Reconciliation Business Logic Pharmaceuticals Data Governance Data Management SAP Applications Safety Assurance Product Strategy Looker Analytics Data Warehousing Data Architecture Advanced Analytics Product Management, * Degree or equivalent experience. Typically requires 9+ years of professional experience and 1+ years of supervisory and/or management experience., * 9+ years of experience in data product management, data architecture, analytics, or a related field and 1+ years supervisory and/or management experience. * Demonstrated experience managing complex and ambiguous data products and ecosystems or enterprise data initiatives. * Strong knowledge and understanding of EDW pipelines, data warehousing concepts, and semantic layer development. * Experience working with SAP, Snowflake, Looker/LookML, or similar enterprise data ecosystems. * Demonstrated expertise in converting business requirements into data product solutions that support advanced analytics and promote scalability. * Effective communication, prioritization, and empowerment skills. * Operational excellence and continuous improvement mindset. * Ability to travel up to 20%., * Experience in healthcare, distribution, or highly regulated industries. * Familiarity with data governance frameworks and regulatory/audit controls. * Background working with large, multi-segment data environments. ## Description Internal Reporting Career Development Strategy Execution Product Requirements Technology Ecosystems Business Requirements Snowflake (Data Warehouse) Healthcare Industry Knowledge Continuous Improvement Process Employee Performance Management, The Senior Manager of the Enterprise Data Warehouse (EDW) for the Enterprise Reporting & Analytics (ERA) platform is responsible for the strategy, execution, and management of the delivery of data products that supports customer-facing analytics and internal reporting. This role ensures delivery of scalable, high-quality, compliant data assets that power analytics, reporting, and decision-making across McKesson's Pharma distribution segments. The Senior Manager partners with MT, engineering, upstream data owners, and business stakeholders to maintain a unified, trusted, and performant data ecosystem., Data Product Strategy & Execution * Lead the full end-to-end lifecycle of EDW data products, including vision, roadmap definition, requirements, delivery, and continuous improvement. * Maintain and evolve EDW architecture, business logic, and semantic layer design (e.g., LookML) aligned to enterprise analytics needs. * Define and drive data product standards, scalable business definitions, and enterprise-aligned data logic. * Translate complex business requirements into actionable technical specifications for engineering and platform teams. * Implement and maintain logic for key EDW fields to ensure accurate data representation across supported USPD segments. * Support the rollout of new data features and enhancements based on defined product requirements and business needs. Data Quality, Governance & Compliance * Establish and maintain data quality metrics, validation processes, and automated checks ensuring accuracy, completeness, and timeliness with MT partners. * Oversee QA/UAT processes including reconciliation and source-system validation. * Ensure alignment with regulatory, legal, audit, and enterprise data governance standards. * Promote adoption of governance frameworks and consistent data management practices across analytics and business teams. Semantic Layer Support * Partner with Product Management and Engineering to implement LookML fields and indicators aligned with EDW logic. * Ensure semantic layer consistency by validating field mappings and business rule alignment. Cross-Functional Collaboration & Stakeholder Engagement * Serve as the primary liaison between technical teams, analytics partners, upstream data owners, and key business stakeholders. * Facilitate discovery, feedback loops, and prioritization discussions to ensure EDW solutions meet business needs. * Drive alignment across multiple partner groups on data logic, definitions, and solution approaches. People Leadership & Team Management * Lead, mentor, and develop a high-performing data product management team. * Establish operational rhythms, documentation processes, and standardized ways of working that support team efficiency and repeatability. * Foster a collaborative, inclusive culture focused on innovation, continuous improvement, and data-driven decision-making. * Provide coaching, performance management, and career development support for direct reports., Irving, TX*Hybrid Auditing Coaching Leadership Management Governance Innovation Scalability Data Quality Communication Prioritization Reconciliation Business Logic Pharmaceuticals Data Governance Data Management SAP Applications Safety Assurance Product Strategy Looker Analytics Data Warehousing Data Architecture Advanced Analytics Product Management Acceptance Testing Internal Reporting Career Development Strategy Execution Product Requirements Technology Ecosystems Business Requirements Snowflake (Data Warehouse) Healthcare Industry Knowledge Continuous Improvement Process Employee Performance Management +0 Director Data Engineering MCKESSON Irving, TX*On-Site DevOps Writing Planning Operations Leadership Automation Governance Innovation Data Lakes Databricks Scalability Data Science Disabilities Communication Observability Data Strategy Data Curation .NET Framework Data Ingestion Data Pipelines Synapse Citrix Pharmaceuticals Microsoft Azure Data Governance Code Generation Data Processing Azure Cosmos DB Computer Science Machine Learning Data Engineering Technical Acumen Incident Response Data Architecture Advanced Analytics Azure Data Factory Financial Services Talent Development Business Decisions Workflow Management Business Objectives Technical Leadership Programming Languages Emerging Technologies Strategic Partnership Business Intelligence Continuous Development Artificial Intelligence Concept Drift Detection Event-Driven Programming SQL (Programming Language) Scala (Programming Language) Python (Programming Language) Vendor Relationship Management Business Intelligence Development ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Developer Tools for Microsoft Azure](https://www.wearedevelopers.com/videos/450-developer-tools-for-microsoft-azure) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [From developer to manager – what does it take to become an engineering manager?](https://www.wearedevelopers.com/magazine/42-from-developer-to-manager-what-does-it-take-to-become-an-engineering-manager) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)