Director Data Management Jobs in Michigan (NOW HIRING)

General Purpose & Essential Duties:

The Director of Data Strategy & AI Implementation is 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 & AI Implementation combines 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. 

Enterprise Data Strategy & Roadmap 

• 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 Onelake build to 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 this cross department team is to ensure high quality data across the operational teams. 

• AI Cost controls and cost projections 

Data Architecture, Engineering & Platform Leadership 

• 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. 

Data Governance, Quality & Security 

• 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. 

Analytics, Business Intelligence & Data Enablement 

• 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. 

Artificial Intelligence & Advanced Analytics Enablement 

• 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 AI initiatives by providing the appropriate data and 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, scalability, risk, and technical fit. 

Acquisition Data Integration 

• Lead the data strategy and technical approach for integrating newly acquired companies into Guardian's enterprise data ecosystem. 

• Establish repeatable frameworks and standards for acquisition-related data discovery, assessment, mapping, migration, validation, and integration. 

• Partner with Business Process & Integration, Finance, Customer Operations, IT, and other stakeholders to understand acquired-company data structures and integration requirements. 

• Identify data quality, architecture, security, and migration risks associated with acquisitions and establish appropriate mitigation plans. 

• Capture lessons learned from integrations and continuously improve Guardian's acquisition data playbook. 

Team Leadership & Development 

• Lead, develop, and support the Data team, establishing clear expectations, priorities, and accountability. 

• Build technical and analytical capability across the team through coaching, mentoring, development planning, and meaningful work assignments. 

• Support workforce planning, recruiting, onboarding, performance management, and succession planning for the Data function. 
• Foster a collaborative, business-oriented culture focused on quality, innovation, accountability, and continuous improvement.  
• Ensure team members understand the business context behind technical work and remain focused on delivering measurable organizational value. 

Business Partnership & Cross-Functional Collaboration  

• Serve as the senior data advisor to the CTO, executive leadership, and business stakeholders. 
• Establish strong working relationships across IT's Software, Infrastructure, and Data functions to ensure technology decisions are coordinated and scalable. 
• Promote a shared-services mindset in which the Data team operates as an enterprise partner rather than an isolated technical function. 

Performance, Value & Continuous Improvement  

• Establish meaningful measures of data-platform health, data quality, delivery effectiveness, adoption, and business value. 
• Monitor progress against the enterprise data roadmap and communicate results, risks, and priorities to the CTO and other stakeholders. 
• Evaluate the return and business impact of significant data initiatives and technology investments. 
• Identify opportunities to simplify architecture, automate processes, reduce technical debt, improve delivery, and increase organizational access to trusted data. 
• Develop repeatable standards, processes, and documentation that support a scalable and sustainable Data function. 

Required Education, Experience, Skills & Abilities  

• Strong strategic leadership with the ability to translate business priorities into an actionable enterprise data roadmap. 
• Strong business and financial acumen with the ability to prioritize technical investments based on organizational value. 
• Strong analytical, problem-solving, and decision-making skills. 
• Exceptional verbal, written, and executive-level presentation skills. 
• Ability to translate complex technical concepts into understandable business language. 
• Ability to balance long-term strategic direction with practical execution in a growing and acquisition-driven organization. 
• Required 8+ years of Integration Architecture and Master Data Management (MDM), ERP and CRM data modeling. Strong entity resolution using fuzzy matching and match-and-merge strategies.  
• Experience designing enterprise Customer 360 solutions, Golden Record architectures, survivorship rules, data mastering strategies, and authoritative source-of-record frameworks across CRM, ERP, and operational systems. 
• Experience building Microsoft Purview Data Map and Purview Data Catalog 
• 3+ years designing Fabric OneLake Medallion architecture with pipelines, notebooks, error handling, master data propagation, certified data products and dataflow design. 
• Dataverse architecture, shortcuts and security organization, event-driven integrations and Azure integration services 
• 5+ years of Azure Cost Management: Cost anomaly detection, budget alerts, cost forecasting.  Fabric Capacity Metrics and Copilot Studio Analytics 
• Complex SQL, ETL/ELT patterns, data validation, and reconciliation.  Ability to diagram relational database pipelines 
• Power BI Semantic models, governance, enterprise reporting enhancements 
• Required working knowledge of GENAI/RAG Concepts model/data requirements focused on: audit logging, security controls and hallucination controls.
• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Business, or related field preferred, or equivalent relevant experience. 
• 8+ years of progressive experience in data engineering, data architecture, analytics, business intelligence, data strategy, or related disciplines. 
• Demonstrated experience developing or executing enterprise data strategies and modernizing data capabilities. 
• Experience with cloud-based data platforms and enterprise data architecture required; Microsoft Azure experience strongly preferred. 
• Experience with data governance, data quality, and enterprise analytics programs required. 
• Experience supporting organizational acquisitions, data migrations, system integrations, or business integrations strongly preferred. 
• Experience with AI/ML initiatives or advanced analytics environments preferred. 
• Master's degree, MBA, or relevant industry certifications preferred but not required.