Head of Enterprise Data, Solutions & Operations

Guardian Life Insurance•New York, NY

4d•Remote

About The Position

The Head of Enterprise Data, Solutions & Operations is accountable for defining and leading Guardian’s enterprise data strategy, engineering execution, and operational delivery across all lines of business. This role owns the end-to-end data ecosystem—including data platforms, data engineering, data products, and data/ML operations—ensuring scalable, reliable, and governed data capabilities that enable business performance and AI-driven outcomes. This leader establishes how data is built, managed, and operated across the enterprise, setting standards for engineering, platform integration, and operational excellence. The role ensures data is delivered as reusable, enterprise assets aligned to business priorities and technology strategy. Operating at the intersection of business and technology, this role partners with senior executives across Product, Architecture, and Value Streams to shape demand, prioritize investment, and deliver measurable outcomes. The Head of Enterprise Data, Solutions & Operations drives consistency, scalability, and accountability across a highly matrixed organization.

Requirements

An enterprise leader in data, engineering, and operations
Strong at influencing senior stakeholders and driving alignment
Experienced in scaling capabilities in complex, matrixed environments
Able to translate strategy into execution and measurable outcomes
15+ years of experience in data, engineering, or technology leadership
Proven experience leading enterprise data platforms, engineering, and operations
Experience building and managing large, cross-functional teams
Strong understanding of cloud, data platforms, APIs, and AI ecosystems
Experience with DataOps/MLOps and federated delivery models
Strong executive presence and stakeholder management skills
Must be legally authorized to work in the United States, without the need for employer sponsorship.

Responsibilities

Define and own the enterprise data strategy across platforms, engineering, and data products
Establish standards for how data is structured, built, governed, and scaled
Drive the transition from fragmented, LOB-specific environments to a unified enterprise data ecosystem
Enable advanced analytics, AI/GenAI, and cross-value stream insights
Lead enterprise data engineering, including pipelines, integrations, and platform capabilities
Oversee development of scalable, cloud-based data platforms
Ensure consistent engineering standards, performance, and reliability
Partner with Architecture to align to enterprise technology direction
Own DataOps and MLOps, including reliability, observability, and incident management
Establish operational standards for data availability, integrity, and performance
Drive proactive monitoring and resolution of enterprise data issues
Define and lead how data capabilities are prioritized, funded, and delivered
Drive alignment across Product, Engineering, Architecture, and Data teams
Enable a federated model through centralized standards and distributed execution
Translate business strategy into scalable data and platform capabilities
Ensure data investments drive measurable outcomes (growth, efficiency, risk)
Drive adoption and track performance and ROI of data and AI initiatives
Lead and scale teams across data engineering, platforms, and operations
Build strong leadership bench and clear accountability structures
Attract and retain top data and engineering talent
Ensure alignment with data governance, security, and regulatory standards
Oversee enterprise data risk, including quality issues and SLA performance