Enterprise Data Architect; EDA

Designed with simplicity in mind, Verkada's six product lines — video security cameras, access control, environmental sensors, alarms, workplace, and intercoms — provide unparalleled building security through an integrated, cloud-based software platform. Over 33,500 organizations, including 96 companies in the Fortune 500, across 93 countries worldwide trust Verkada as their physical security layer for easier management, intelligent control, and scalable deployments.

Founded in 2016 with more than $700M in funding raised to-date, Verkada has expanded rapidly with 15 offices and 2,200+ full-time employees.

The Enterprise Data Architect (EDA) is responsible for defining and advancing the company’s enterprise-wide data strategy across all non-product engineering business functions.

In this role, the EDA will lead the development of a comprehensive framework to design, implement, and govern enterprise data. This effort will integrate diverse business systems, unify fragmented data, and provide accurate, trusted, and easily accessible information to empower decision-making and drive operational excellence.

The EDA will define and champion the enterprise-wide data governance framework, aligning business and technology needs to deliver seamless processes for functional leaders and empower technical teams to create scalable, future-ready solutions.

This role is especially critical in a fast-growing organization
, where data consistency and reliability are foundational to operational excellence and future scalability.

• Data Strategy & Architecture
  • Define and own the enterprise data strategy in alignment with corporate goals.
  • Design and maintain comprehensive data architecture spanning ERP, HRIS, CRM, ATS, Finance, and other core business systems.
  • Ensure the architecture supports scalability, performance, and resilience as the company grows.
  • Lead initiatives to break down data silos and establish trusted,
    unified sources of truth across the organization – this may include building a enterprise-wide data warehouse.
• Data Governance & Stewardship
  • Champion a company-wide data governance framework that fosters a culture of data accountability—defining clear policies, ownership, stewardship, quality standards, and lifecycle management to ensure data is trusted and actionable.
  • Facilitate Regular Meetings: Schedule recurring governance council sessions with functional leaders, data stewards, and technical specialists to review priorities, align on decisions, and resolve data issues.
  • Drive
    
    Cross-Functional Collaboration:
    
    Act as the bridge between business and technology teams to ensure shared accountability for data quality and consistency.
  • Identify & Track Data Gaps: Continuously monitor for data inconsistencies, missing attributes, or system misalignments across source systems.
  • Coordinate Remediation Efforts: Work with system owners and data stewards to resolve data gaps and improve data accuracy.
  • Implement Monitoring & Alerts: Establish automated data quality checks and exception reporting to proactively detect and address issues.
  • Maintain Governance Policies: Keep data ownership, stewardship, and lifecycle management policies up to date.
  • Ensure Compliance: Monitor adherence to data standards and escalate when policies are not followed.
  • Measure Effectiveness: Track key data governance KPIs such as data quality scores, reconciliation error rates, and time-to-resolution for data issues.
  • Continuously Improve: Refine governance processes, adjust frameworks, and adopt new tools or methodologies to enhance efficiency and impact.
• Data Integration & Unification
  • Champion the adoption of a Universal Data Model and ensure consistent definitions across all systems.
  • Steer the design and implementation of integrations between business systems using APIs, middleware, and event-driven architectures.
  • Coordinate data orchestration pipelines to unify, cleanse, and harmonize data from multiple sources.
• Evaluate emerging data technologies, tools, and best practices to recommend innovative solutions that drive efficiency and insight.
• Continuously improve data quality, monitoring frameworks, and performance metrics.
• Le…