Director, Data Products & Engineering, Operations NA

Vantage Data Centers•Denver, CO

39d•$180,000 - $200,000•Hybrid

About The Position

The 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. Operational Excellence at Vantage is hands-on and impact-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. This role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible). The Director, Operations Data Products & Engineering leads the data product management and technical delivery capability for North America Operations. This role owns the integrated Operations data product portfolio and roadmap, translating operational priorities and intelligence requirements into trusted, scalable, and reusable products that improve how Operations plans, executes, predicts, and makes decisions. Reporting to the Vice President of Operational Excellence, the Director builds and leads a multidisciplinary capability spanning data product management, data engineering, analytics engineering, business intelligence, governance, and solution delivery. As the portfolio evolves, the Director may establish dedicated product leadership for priority domains based on their scale, complexity, and strategic importance. Serving 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 domain products, technical priorities, delivery outcomes, and value realization while leveraging, rather than duplicating, enterprise capabilities.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Engineering, Business, Product Management, or a related field required.
Ten or more years of progressive experience in data products, product management, data engineering, analytics, enterprise data platforms, business intelligence, or a related discipline.
Five or more years of experience leading multidisciplinary product or technical teams, programs, or product portfolios.
Demonstrated experience developing product strategies and roadmaps and delivering data, analytics, digital, or AI products tied to measurable business outcomes.
Experience establishing or scaling product management, engineering, governance, and delivery practices.
Experience leading product managers, product owners, or cross-functional teams responsible for distinct product domains.
Experience operating within a federated or hub-and-spoke model and partnering with centralized enterprise technology teams.
Experience delivering solutions within modern cloud data, lakehouse, integration, analytics, automation, or AI ecosystems.
Experience managing external engineering, analytics, product, or technology delivery partners.
Strong understanding of product management, data product management, data engineering, Strong knowledge of product management, data engineering, analytics engineering, data architecture, semantic modeling, business intelligence, governance, automation, and AI enablement.
Ability to build a product management capability that balances focused product ownership with coordinated portfolio governance.
Ability to translate complex operational needs into clear product strategies, technical roadmaps, investment priorities, and executable delivery plans.
Strong portfolio management and prioritization skills, including evaluating competing needs, dependencies, capacity, risk, readiness, and business value.
Strong business and technical judgment, with the ability to balance immediate delivery needs with long-term capability development.
Ability to lead through influence across business, technology, operational, enterprise platform, and external partner organizations.
Strong executive communication, stakeholder management, negotiation, and decision-making skills.
Ability to communicate complex data, product, technology, and AI concepts clearly to technical and nontechnical audiences.
Strong people leadership skills, including organization design, talent development, coaching, performance management, and team building.
High degree of ownership, accountability, curiosity, and comfort operating in a complex and evolving environment.

Nice To Haves

Master’s degree in a related technical or business discipline preferred.
Relevant technical, data management, cloud-platform, product-management, or agile certifications are a plus.
Experience with operational, telemetry, asset, infrastructure, industrial, or data-center environments strongly preferred.
Experience advancing capabilities from traditional reporting toward predictive analytics, intelligent automation, or AI-enabled solutions preferred.

Responsibilities

Own and manage the integrated Operations data product portfolio and multiyear roadmap.
Translate Operations strategy, business priorities, and intelligence requirements into coordinated product strategies, use cases, investment priorities, and delivery plans.
Establish a product management operating model with clear roles, decision rights, lifecycle practices, and governance across product, engineering, business, and enterprise technology teams.
Establish and oversee dedicated product leadership for priority domains as the portfolio matures, with accountability for product vision, roadmaps, requirements, adoption, and value realization.
Implement a disciplined intake, evaluation, prioritization, and sequencing process for Operations data, analytics, engineering, automation, and AI needs.
Make portfolio investment and capacity decisions based on operational value, strategic alignment, feasibility, risk, readiness, reuse, and available resources.
Balance immediate delivery priorities with foundational investments in scalability, data quality, interoperability, and future capabilities.
Manage products throughout their lifecycle, from discovery and development through adoption, enhancement, sustainment, consolidation, or retirement.
Lead the design and delivery of Operations data products, including governed pipelines, domain data models, semantic layers, telemetry integrations, analytics, dashboards, intelligent workflows, and AI-ready datasets.
Translate product strategies and business requirements into scalable technical solutions in partnership with Global Data & AI, Enterprise Architecture, platform owners, and source-system teams.
Establish cross-functional product teams aligned to prioritized operational outcomes, with coordinated roadmaps, backlogs, release plans, and success measures.
Develop reusable technical patterns and shared components that reduce fragmented development, one-off reporting, and duplicative solutions.
Establish development and lifecycle practices that support product reliability, performance, security, scalability, interoperability, maintainability, and user experience.
Identify and resolve delivery dependencies, capacity constraints, architectural decisions, and cross-product conflicts.
Oversee external delivery partners and vendors, ensuring accountability for technical quality, product outcomes, knowledge transfer, and sustainable internal ownership.
Serve as the primary Operations partner to Global Data & AI, representing Operations priorities, dependencies, capacity requirements, and future capability needs.
Align the Operations data product roadmap with enterprise architecture, data platforms, shared engineering services, governance standards, security requirements, and AI strategy.
Maintain clear accountability within the hub-and-spoke operating model, with Global Data & AI owning shared enterprise platforms and services and Operations owning its domain products, priorities, adoption, and outcomes.
Coordinate decisions involving shared data sources, integrations, engineering capacity, platform constraints, common AI services, and cross-functional dependencies.
Ensure Operations effectively leverages enterprise capabilities while avoiding disconnected, duplicative, or unsustainable solutions.
Establish governance practices for the Operations data product portfolio in alignment with enterprise policies and standards.
Partner with Operations Intelligence, product leads, business data product owners, data owners, and stewards to define domain models, business rules, authoritative sources, ownership, and data-quality expectations.
Ensure the technical implementation of approved KPI definitions, calculations, semantic models, decision logic, and reporting standards.
Establish visibility into data quality, lineage, metadata, access, product health, adoption, value, and issue resolution.
Embed security, controls, quality assurance, and applicable risk and regulatory requirements throughout the product lifecycle.
Define the evolution of Operations capabilities from foundational reporting toward predictive and prescriptive insights, intelligent automation, and AI-enabled decision support.
Establish reusable data, telemetry, integration, analytics, and AI foundations that support multiple products and future use cases.
Identify and advance opportunities involving forecasting, anomaly detection, intelligent workflows, automation, AI agents, and operational decision support.
Evaluate prospective use cases with operations intelligence, product leads, and functional leaders based on operational value, feasibility, scalability, risk, and organizational readiness.
Transition successful pilots and experiments into governed, secure, scalable, and supportable production capabilities.
Monitor emerging data, AI, automation, telemetry, and operational technology practices relevant to data-center operations.
Build and lead a multidisciplinary capability spanning data product management, data engineering, analytics engineering, business intelligence, solution delivery, and data governance.
Determine the appropriate mix of internal talent, enterprise services, embedded resources, and external delivery support.
Establish clear roles, decision rights, and ways of working across Data Products & Engineering, Operations Intelligence, Global Data & AI, Operations functions, and other enterprise partners.
Recruit, develop, and coach product and technical professionals capable of owning complex products and influencing senior business and technology stakeholders.
Ensure product leaders have sufficient authority to drive product outcomes within appropriate portfolio, architecture, investment, and enterprise governance.
Set clear performance expectations and foster a culture of accountability, curiosity, customer focus, technical excellence, and continuous improvement.
Build strong working relationships with senior Operations, Technology, Product, Reliability Engineering, and enterprise data leaders.
Perform additional duties as assigned by management.

Benefits

medical, dental, and vision coverage
life and AD&D
short and long-term disability coverage
paid time off
employee assistance
participation in a 401k program that includes company match
many other additional voluntary benefits
above market total compensation package
comprehensive suite of health and welfare, retirement, and paid leave benefits exceeding local expectations
recognition, training and development