Director, Data Analytics & Engineering, Operations NA

About Vantage

Vantage 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.

Operational Excellence Department

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.

Position Overview

This role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible).

The Director, Operations Data Analytics & Engineering leads the management and technical delivery capability for North America Operations. This role owns the integrated Operations data portfolio and roadmap, translating operational priorities and intelligence requirements into trusted, scalable, and reusable solutions 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 delivery management, data engineering, analytics engineering, business intelligence, governance, and solution delivery. As the portfolio evolves, the Director may establish dedicated 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 data deliverables , technical priorities, outcomes, and value realization while leveraging , rather than duplicating, enterprise capabilities.

Essential Job Functions

Data Strategy and Portfolio Management

Own and manage the integrated Operations data portfolio and multiyear roadmap.

Translate Operations strategy, business priorities, and intelligence requirements into coordinated delivery strategies, use cases, investment priorities, and development plans.

Establish and oversee dedicated leadership for priority functional domains as the portfolio matures, with accountability for data strategy vision, roadmaps, requirements, adoption, and value realization.

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 data solutions throughout their lifecycle, from discovery and development through adoption, enhancement, sustainment, consolidation, or retirement.

Data Engineering & Delivery

Lead 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.

Translate data strategy and business requirements into scalable technical solutions in partnership with Global Data & AI, Enterprise Architecture, platform owners, and source-system teams.

Establish cross-functional 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 solution 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, solution outcomes, knowledge transfer, and sustainable internal ownership.

Global Data & AI Alignment

Serve as the primary Operations partner to Global Data & AI, representing Operations priorities, dependencies, capacity requirements, and future capability needs .

Align the Operations data 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 solutions, 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 .

Data Governance and Product Quality

Establish governance practices for the Operations data portfolio in alignment with enterprise policies and standards.

Partner with Operations Intelligence, leads, business 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, health, adoption, value, and issue resolution.

Embed security, controls, quality assurance, and applicable risk and regulatory requirements throughout the development lifecycle.

Advanced Data and AI Capabilities

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 capabilities, solutions 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 o perations i ntelligence, 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.

Organizational and Team Leadership

Build and lead a multid