Chief Data Strategist

Verizon•Irving, TX

1d•$176,500 - $339,000•Hybrid

About The Position

The Senior Director of Data Strategy & Technology is a critical executive leader responsible for shifting Verizon’s data organization architecture-driven powerhouse. This role will directly spearhead the transition to a Governed Federated Model, establishing a single source of truth for all strategic and operational data. By championing connected architecture and unified data, this leader creates the foundation our enterprise needs to thrive with high-velocity AI and advanced analytics.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
Minimum of 10 years of progressive leadership experience in enterprise data strategy, large-scale cloud data migrations (Google Cloud preferred), or data infrastructure optimization.
7+ years in a senior leadership role managing large, distributed teams.
Mastery of the Modern Data Stack, data fabric/mesh concepts, enterprise architecture, and experience managing hyper-scaled data footprints (hundreds of terabytes to petabytes).
Exceptional executive presence with a proven track record of influencing cross-functional SVPs, VPs, and technical stakeholders to adopt centralized standards.
Demonstrated success steering organizations through complex operational turnarounds, reducing legacy technical debt, and managing high-stress transformation teams.
Demonstrated ability to develop and execute strategic plans and drive innovation within a complex organizational structure.
Experience managing budgets and vendor relationships within a large corporate environment.
Ability to work effectively in a fast-paced and complex environment with multiple stakeholders across different Verizon business units.
Strong business acumen with excellent influencing and negotiation skills.

Nice To Haves

Master of Business Administration or Master’s degree in a technical area of study
15+ years of progressive leadership experience in enterprise data strategy, large-scale cloud data migrations (Google Cloud preferred), or data infrastructure optimization.
Experience within the telecommunications industry.
Familiarity with Verizon's internal systems and processes.

Responsibilities

Lead the strategic rollout of the new Governed Federated Model across Verizon, directly engaging with VPs and SVPs across business units to integrate localized data operations into a centralized framework.
Oversee the functional transition of data teams, moving from a legacy mirrored geographic structure to a streamlined, functional model to reduce complexity and foster absolute accountability.
Manage the strategic demand intake to balance critical Business-As-Usual (BAU) operational deliverables with high-intensity "Transformation Tiger Team" initiatives.
Directly address and eliminate massive data duplication across the enterprise, systematically shutting down non-federated spaces.
Expand the Google Cloud single source of truth by integrating critical external data assets—including legacy SQL Servers, Oracle Databases, and other third-party systems—into a unified, enterprise-wide framework.
Champion the creation and adoption of a single, authoritative shared data sandbox equipped with automated quality controls and seamless discoverability, replacing over 100+ non-federated sandboxes.
Drive engineering rigor to collapse and organize a legacy landscape of 300K+ tables into a highly organized, highly discoverable technical framework.
Define the technical standards and architectural roadmaps required to transition the business to a modern, agile, and secure data infrastructure.
Partner with global engineering teams to identify and train federated data engineers on common data standards, ensuring only certified builders can deploy within the shared sandbox environment.
Optimize the data ecosystem on Google Cloud, building the underlying data tech stack necessary to seamlessly enable and scale enterprise AI applications.
Procure, assemble, and integrate best-in-class technology capabilities to establish a modern, enterprise-grade data engineering ecosystem.
Architect and implement the core tech capabilities—including automated quality controls, embedded governance, and full operational observability—that enable resilient, high-performance data pipelines across heterogeneous environments.
Drive the adoption of conversational AI and natural language interfaces, enabling intuitive data discovery, querying, and interaction for technical and non-technical stakeholders alike.