{"id":187396,"url":"https://alion.io/job/vantage-data-centers-director-data-products-engineering-operations-na","title":"Director, Data Analytics & Engineering, Operations NA","company":{"id":8762,"name":"Vantage Data Centers","domain":"vantagedc.com","url":"https://alion.io/company/vantagedc","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":26,"ghost_share":0,"stale_share":0.731,"repost_share":0.038,"time_to_fill_p50_days":29,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Denver, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":210000,"currency":"USD","period":"year","gross":null,"usd_annual":210000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":true},{"name":"Copilot Studio","optional":true},{"name":"Databricks","optional":true},{"name":"Master Data Management","optional":true},{"name":"Microsoft Fabric","optional":true},{"name":"Power BI","optional":true},{"name":"ServiceNow","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-09-01T21:54:05Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-10-22T01:21:32Z","board_verified":true,"closed_at":null,"days_open":50,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":50},"description":"About Vantage\nVantage powers, cools, protects and connects the technology of the world’s well-known hyperscalers, cloud providers and large enterprises. Developing and operating across North America, EMEA and Asia Pacific, Vantage has evolved data center design in innovative ways to deliver dramatic gains in reliability, efficiency and sustainability in flexible environments that can scale as quickly as the market demands.\nOperational ExcellenceDepartment\nThe Operational Excellence team establishes the systems, practices, and culture that enable Vantage to operate at scale across North America with consistency, quality, and speed. We strengthen the scalability and effectiveness of NA Operations - including Mission Critical Operations, Sales Engineering, Customer Experience, and Design Integration - by partnering with business leaders and global functions to standardize how we work, drive process excellence, deliver strategic programs, enable data-driven decisions, and embed continuous improvement and transformation.\nOperational Excellence at Vantage is hands-on andimpact-driven. We blend delivery discipline, systems thinking, and best-in-class operational practices to address root causes, improve efficiency, and accelerate outcomes. Our team members lead high-impact initiatives, shape cross-functional ways of working, and directly influence how Vantage delivers on its growth, operational, and customer commitments.\nPosition Overview\nThis role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible).\nThe Director, Operations DataAnalytics& Engineeringleads themanagement and technical delivery capability for North America Operations. This role owns the integrated Operations dataportfolio and roadmap, translating operational priorities and intelligence requirements into trusted, scalable, and reusablesolutionsthat improve how Operations plans, executes, predicts, and makes decisions.\nReporting to the Vice President of Operational Excellence, the Director builds and leads a multidisciplinary capability spanningdeliverymanagement, data engineering, analytics engineering, business intelligence, governance, and solution delivery. As the portfolio evolves, the Director mayestablishdedicatedleadership for priority domains based on their scale, complexity, and strategic importance.\nServing as the primary Operations counterpart to Global Data & AI, the Director aligns Operations priorities with enterprise data and AI roadmaps, platforms, architecture, standards, and services. The role is accountable for Operations domaindatadeliverables, technical priorities,outcomes, and value realization whileleveraging, rather than duplicating, enterprise capabilities.\nEssential Job Functions\nData Strategy and Portfolio Management\nOwn and manage the integrated Operations data portfolio and multiyear roadmap.\n\nTranslate Operations strategy, business priorities, and intelligence requirements into coordinated delivery strategies, use cases, investment priorities, and development plans.\n\nEstablish and oversee dedicated leadership for priority functional domains as the portfolio matures, with accountability for data strategy vision, roadmaps, requirements, adoption, and value realization.\n\nEstablish and oversee dedicated product leadership for priority domains as the portfolio matures, with accountability for product vision, roadmaps, requirements, adoption, and value realization.\n\nImplement a disciplined intake, evaluation, prioritization, and sequencing process for Operations data, analytics, engineering, automation, and AI needs.\n\nMake portfolio investment and capacity decisions based on operational value, strategic alignment, feasibility, risk, readiness, reuse, and available resources.\n\nBalance immediate delivery priorities with foundational investments in scalability, data quality, interoperability, and future capabilities.\n\nManage data solutions throughout their lifecycle, from discovery and development through adoption, enhancement, sustainment, consolidation, or retirement.\n\nData Engineering & Delivery\nLead the design and delivery of Operations data solutions, including governed pipelines, domain data models, semantic layers, telemetry integrations, analytics, dashboards, intelligent workflows, and AI-ready datasets.\n\nTranslate data strategy and business requirements into scalable technical solutions in partnership with Global Data & AI, Enterprise Architecture, platform owners, and source-system teams.\n\nEstablish cross-functional teams aligned to prioritized operational outcomes, with coordinated roadmaps, backlogs, release plans, and success measures.\n\nDevelop reusable technical patterns and shared components that reduce fragmented development, one-off reporting, and duplicative solutions.\n\nEstablish development and lifecycle practices that support solution reliability, performance, security, scalability, interoperability, maintainability, and user experience.\n\nIdentify and resolve delivery dependencies, capacity constraints, architectural decisions, and cross-product conflicts.\n\nOversee external delivery partners and vendors, ensuring accountability for technical quality, solution outcomes, knowledge transfer, and sustainable internal ownership.\n\nGlobal Data & AI Alignment\nServe as the primary Operations partner to Global Data & AI, representing Operations priorities, dependencies, capacity requirements, and future capabilityneeds.\n\nAlign the Operations data roadmap with enterprise architecture, data platforms, shared engineering services, governance standards, security requirements, and AI strategy.\n\nMaintain clear accountability within the hub-and-spoke operating model, with Global Data & AI owning shared enterprise platforms and services and Operations owning its domain solutions, priorities, adoption, and outcomes.\n\nCoordinate decisions involving shared data sources, integrations, engineering capacity, platform constraints, common AI services, and cross-functional dependencies.\n\nEnsure Operations effectively leverages enterprise capabilities while avoiding disconnected, duplicative, or unsustainable solutions.\n\nData Governance and Product Quality\nEstablish governance practices for the Operations data portfolio in alignment with enterprise policies and standards.\n\nPartner with Operations Intelligence, leads, business data owners, and stewards to define domain models, business rules, authoritative sources, ownership, and data-quality expectations.\n\nEnsure the technical implementation of approved KPI definitions, calculations, semantic models, decision logic, and reporting standards.\n\nEstablish visibility into data quality, lineage, metadata, access, health, adoption, value, and issue resolution.\n\nEmbed security, controls, quality assurance, and applicable risk and regulatory requirements throughout the development lifecycle.\n\nAdvanced Data and AI Capabilities\nDefine the evolution of Operations capabilities from foundational reporting toward predictive and prescriptive insights, intelligent automation, and AI-enabled decision support.\n\nEstablish reusable data, telemetry, integration, analytics, and AI foundations that support multiple capabilities, solutions and future use cases.\n\nIdentify and advance opportunities involving forecasting, anomaly detection, intelligent workflows, automation, AI agents, and operational decision support.\n\nEvaluate prospective use cases withoperationsintelligence, product leads, and functional leaders based on operational value, feasibility, scalability, risk, and organizational readiness.\n\nTransition successful pilots and experiments into governed, secure, scalable, and supportable production capabilities.\n\nMonitor emerging data, AI, automation, telemetry, and operational technology practices relevant to data-center operations.\n\nOrganizational and Team Leadership\nBuild and lead a multidisciplinary capability spanning lifecycle management, data engineering, analytics engineering, business intelligence, solution delivery, and data governance.\n\nDetermine the appropriate mix of internal talent, enterprise services, embedded resources, and external delivery support.\n\nEstablish clear roles, decision rights, and ways of working across Data Analytics & Engineering, Operations Intelligence, Global Data & AI, Operations functions, and other enterprise partners.\n\nRecruit, develop, and coach functional and technical professionals capable of owning complex solutions and influencing senior business and technology stakeholders.\n\nEnsure team members have sufficient authority to drive solution outcomes within appropriate portfolio, architecture, investment, and enterprise governance.\n\nSet clear performance expectations and foster a culture of accountability, curiosity, customer focus, technical excellence, and continuous improvement.\n\nBuild strong working relationships with senior Operations, Technology, Product, Reliability Engineering, and enterprise data leaders.\n\nAdditional Duties\nPerform additional duties as assigned by management.\n\nJob Requirements\nEducation\nBachelor’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Business, Product Management, or a related field required.\n\nMaster’s degree in a related technical or business discipline preferred.\n\nRelevant technical, data management, cloud-platform, product-management, or agile certifications are a plus.\n\nExperience\nTen or more years of progressive experience in dataanalytics,dataengineering, productmanagement,,analytics, enterprise data platforms, business intelligence, or a related discipline.\n\nFive or more years of experience leading multidisciplinaryfunctionalor technical teams, programs, ordata solutionportfolios.\n\nDemonstrated experience developingdatastrategies and roadmaps and delivering data, analytics, digital, or AIsolutionstied to measurable business outcomes.\n\nExperienceestablishingor scalingdatamanagement, engineering, governance, and delivery practices.\n\nExperience leadingor cross-functional teams responsible for distinctdatadomains.\n\nExperience operating within a federated or hub-and-spoke model and partnering with centralized enterprise technology teams.\n\nExperience delivering solutions within modern cloud data,lakehouse, integration, analytics, automation, or AI ecosystems.\n\nExperience managing external engineering, analytics,application, or technology delivery partners.\n\nExperience with operational, telemetry, asset, infrastructure, industrial, or data-center environments strongly preferred.\n\nExperience advancing capabilities from traditional reporting toward predictive analytics, intelligent automation, or AI-enabled solutions preferred.\n\nSkills\nStrong knowledge of data engineering, analytics engineering, data architecture, semantic modeling, business intelligence, governance, automation, and AI enablement.\n\nExperience delivering solutions across modern cloud data, lakehouse, integration, analytics, governance, automation, and AI ecosystems, with working knowledge of platforms and capabilities such as Microsoft Fabric / Azure, Databricks or Snowflake, Power BI, ServiceNow, Power Platform, Copilot Studio, data catalog, lineage, metadata management, data quality, access-control, master data management, telemetry platforms, and operational systems such as CMMS / EAM\n\nAbility to build a capability that balances focused data solution ownership with coordinated portfolio governance.\n\nAbility to translate complex operational needs into clear strategies, technical roadmaps, investment priorities, and executable delivery plans.\n\nStrong portfolio management and prioritization skills, including evaluating competing needs, dependencies, capacity, risk, readiness, and business value.\n\nStrong business and technical judgment, with the ability to balance immediate delivery needs with long-term capability development.\n\nAbility to lead through influence across business, technology, operational, enterprise platform, and external partner organi...","description_format":"text","description_chars":15130,"description_truncated":true,"requirements":{"experience_years_min":10,"management_years_min":5,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["401k plan","Flexible schedule"],"hiring_locations":[{"name":"United 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