Director - Data, Analytics & AI

Talent Team•Escondido, CA

18h•$175,000 - $200,000

About The Position

The Director, Data, Analytics & AI provides strategic and operational leadership for Baker Electric’s enterprise data, analytics, integration, and artificial intelligence capabilities. The Director establishes the vision, architecture, governance, talent, platforms, and delivery practices required to make trusted information available across the company and enable responsible, value-focused AI adoption. The role oversees the enterprise data platform, data engineering, integrations, data governance framework, analytics enablement, AI governance, enterprise AI capabilities, and the relevant vendor ecosystem. This leader initially manages two Data Engineers and one AI Analyst, with anticipated growth as Baker’s data, integration, analytics, and AI capabilities mature.

Requirements

Bachelor’s degree in information systems, data science, computer science, engineering, business, or a related discipline, or equivalent relevant experience.
Ten or more years of progressive experience across data, analytics, integration, enterprise architecture, business intelligence, or AI.
Five or more years of leadership experience.
Demonstrated experience building or operating enterprise data platforms and integration capabilities.
Experience with analytics governance, data quality, master data, and distributed reporting models.
Practical experience with enterprise AI strategy, governance, adoption, or implementation.
Strong vendor, budget, and professional services management experience.

Nice To Haves

Microsoft Fabric, Azure, Power BI, and Microsoft AI ecosystem experience strongly preferred.
Construction or project-based industry experience preferred.

Responsibilities

Develop and maintain a multiyear strategy and roadmap for enterprise business applications.
Ensure application roadmaps align with company goals, operational needs, vendor direction, integration requirements, cybersecurity standards, and data strategy.
Partner with business application owners to optimize commercial platforms before pursuing customization or new systems.
Lead application lifecycle planning, rationalization, renewal, replacement, and retirement.
Monitor vendor product roadmaps, including embedded AI capabilities, and assess their relevance to Baker.
Lead the architecture, evolution, reliability, scalability, and appropriate use of the enterprise data platform.
Establish data architecture, modeling, ingestion, transformation, storage, lineage, quality, and access standards.
Oversee Baker’s Microsoft Fabric environment and associated services and partners.
Ensure architecture decisions support analytics, integrations, AI readiness, security, maintainability, and cost effectiveness.
Manage the professional services relationship supporting data architecture and delivery.
Own enterprise integration strategy, patterns, architecture, engineering, monitoring, and lifecycle management.
Lead integration delivery through internal data engineers and external partners.
Establish standards for APIs, scheduled data movement, error handling, documentation, monitoring, security, and support.
Partner with the Applications team and business system owners to translate functional requirements into supportable integrations.
Maintain transparency into integration dependencies, technical debt, risks, and capacity.
Establish and operate Baker’s enterprise data governance framework.
Define decision rights, standards, stewardship practices, definitions, ownership expectations, issue escalation, and data quality measures.
Coordinate master data governance across applications and business functions.
Reinforce that business functions own the meaning and quality of their data, while the Data, Analytics & AI team owns the governance framework, enabling platforms, architecture, and stewardship coordination.
Partner with application owners and business data stewards to resolve cross-functional data issues.
Establish the enterprise approach to analytics, reporting, semantic models, metrics, dashboards, self-service enablement, and data literacy.
Ensure enterprise metrics have agreed definitions and accountable business owners.
Support business analysts and distributed analytics contributors with governed data products, standards, training, and reusable capabilities.
Avoid centralizing all report development within IT.
Prioritize analytics efforts based on business value, data readiness, reuse, and scalability.
Lead Baker’s enterprise AI strategy, roadmap, governance model, use-case intake, evaluation standards, and value measurement.
Oversee enterprise AI capabilities such as Microsoft Copilot, AI agents, AI-enabled analytics, and approved cross-functional AI platforms.
Partner with Applications on AI features embedded in enterprise applications.
Partner with IT Operations, Cybersecurity & Compliance, Legal, HR, and business owners to assess privacy, security, regulatory, intellectual property, data, and people impacts.
Establish responsible AI practices without creating unnecessary barriers to innovation.
Define pilots with measurable hypotheses, expected outcomes, owners, risk controls, and exit criteria.
Monitor adoption, business value, usage, risk, and ongoing appropriateness.
Maintain awareness of relevant data, AI, automation, and emerging technology trends.
Develop a disciplined process for identifying, assessing, piloting, scaling, or discontinuing emerging capabilities.
Collaborate with business technology leaders to identify opportunities within estimating, preconstruction, VDC/BIM, project execution, field operations, finance, human capital, and operational support.
Distinguish strategic innovation from novelty-driven technology acquisition.
Manage data, analytics, integration, and AI vendors and professional services partners.
Participate in vendor selection, contracts, renewals, performance management, and escalations.
Develop and manage budgets, forecasts, licensing plans, partner capacity, and investment recommendations.
Assess whether capabilities should be delivered internally, through commercial platforms, or with strategic partners.
Work as a peer with the Director, Business Applications & PMO and Director, IT Operations.
Ensure data, integration, analytics, and AI initiatives incorporate application ownership, infrastructure, cybersecurity, compliance, support, business process, and adoption requirements.
Partner with Operational Excellence, Construction Applications, Finance, Human Capital, Construction Applications, Preconstruction, VDC/BIM, field and project execution, and other business technology leaders.
Help shape enterprise recommendations without positioning the Data, Analytics & AI function above other technology domains.
Lead, coach, and develop data engineering and AI team members.
Establish clear roles, technical standards, delivery practices, career paths, documentation expectations, and succession plans.
Scale the team thoughtfully through internal development, hiring, business-embedded capabilities, and professional services partners.
Build a culture that combines technical excellence, business curiosity, responsible innovation, and reliable execution.