Director, Data Strategy

The Director of Data Strategy & AIImplementationis responsible for leading Guardian Alarm's enterprise data function and establishing the strategy, architecture, governance, and capabilities necessary to make data a trusted and accessible business asset. Reporting to the Chief Technology Officer, this role leads the Data team and partners across the organization to ensure data is effectively captured, governed, integrated, secured, and leveraged to support business performance, customer experience, operational efficiency, acquisitions, and long-term growth.

The Director of Data Strategy & AIImplementationcombines strategic leadership with strong technical and business acumen, translating organizational priorities into a practical data roadmap and ensuring the underlying data environment can support analytics, business intelligence, artificial intelligence, machine learning, and emerging business needs. This role also plays a critical part in Guardian's acquisition strategy by establishing scalable approaches for integrating acquired-company data into Guardian's enterprise ecosystem.

• Develop, maintain, and execute Guardian's enterprise data strategy in alignment with organizational priorities and the broader technology roadmap.
• Establish a multi-year roadmap for data architecture, analytics, business intelligence, governance, AI/ML enablement, and related data capabilities.
• Partner with the CTO and business leaders to identify high-value opportunities where data can improve business performance, operational efficiency, customer experience, and decision-making.
• Translating business needs into scalable data capabilities, priorities, and investments.
• Evaluate the effectiveness and business value of data initiatives and adjust priorities based on organizational needs and measurable outcomes.
• Maintain awareness of emerging data technologies and industry trends and determine their appropriate application within Guardian's environment.
• Spearhead the MS Fabric Onelakebuildto ensure a single source of truth across various legacy and modern platforms.
• Lead the Center of Excellence for Data and AI committee with members across the organization, the objective of thiscross department team is to ensure high qualitydataacross the operational teams.
• AI Cost controls and cost projections

• Provide leadership and direction for Guardian's enterprise data architecture, ensuring data platforms are scalable, reliable, secure, maintainable, and aligned with business needs.
• Establish standards and architectural principles for data ingestion, transformation, storage, modeling, integration, and consumption.
• Ensure data pipelines, integrations, models, and platforms support reliable access to high-quality data across the organization.
• Partner with Software and Infrastructure teams to ensure effective integration between applications, enterprise systems, cloud platforms, and the data environment.

• Establish and oversee enterprise data governance practices, including data ownership, stewardship, quality, classification, access, retention, and appropriate use.
• Partner with IT and business stakeholders to ensure data security and privacy requirements are incorporated into data architecture, platforms, and processes.
• Define appropriate access controls and data-management practices for sensitive, confidential, and regulated information.
• Partner with business leaders to establish accountability for data quality and appropriate data stewardship within their respective functions.

• Provide leadership for enterprise analytics, reporting, and business intelligence capabilities that improve organizational decision-making.
• Partner with business leaders to identify meaningful metrics, KPIs, dashboards, and analytical capabilities that support business performance.
• Promote appropriate self-service analytics while maintaining data consistency, security, and governance.
• Help business stakeholders translate complex data into meaningful insights and actionable business decisions.

• Establish the data foundation and governance necessary to responsibly support artificial intelligence, machine learning, predictive analytics, and other advanced analytical capabilities.
• Partner with technical teams and business stakeholders to identify and prioritize practical AI and ML use cases aligned with measurable business needs.
• Support vendor selection and vendor management for AI initiatives ensuring company objectives are met. Support vendor ML and AIinitiativesby providing the appropriate dataand partner with vendors for successful implementation.
• Ensure appropriate data quality, architecture, security, and governance are considered throughout AI and machine-learning initiatives.
• Guide evaluation and adoption of emerging data and AI technologies based on business value,…