Director, Analytics, Insights, & AI at Rheem Manufacturing Company in Atlanta, GA, United States

Job description

• The Director, Analytics, Insights & AI is a senior technology leader responsible for shaping and executing Rheem's enterprise data, analytics, and artificial intelligence strategy. Reporting to the Sr. Director of Platforms, Data, AI & Architecture, this leader will own the Enterprise Data Platform (EDP), advance Power BI adoption across the business, and drive AI/ML initiatives that deliver measurable operational and commercial value. The role requires equal parts strategic vision, technical depth, and the ability to build deep, trust-based relationships with business stakeholders across manufacturing, supply chain, finance, sales, and HR.
• This individual will lead the Data Analytics & AI Center of Excellence (CoE), govern data quality and master data management (MDM), and orchestrate AI engineering pipelines using Azure AI Foundry and MLOps best practices. The Director will manage a team of approximately 8–10 analytics and AI professionals and will be accountable for budget, vendor relationships, and emerging technology evaluation within the analytics and AI domain.
• This position will serve Rheem North America, and located in Atlanta, GA (hybrid). This role follows our hybrid work arrangement, with team members working in the office Monday through Thursday and remotely on Fridays.

Responsibilities

• Enterprise Data, Analytics & AI Strategy
• Define and execute a multi-year enterprise data, analytics, and AI roadmap aligned to Rheem's business priorities across manufacturing, commercial, and support functions.
• Partner with the Sr. Director of Platforms, Data, AI & Architecture to integrate data strategy into the broader technology vision.
• Serve as a thought leader on emerging analytics, AI/ML, and generative AI trends within the industrial manufacturing and HVAC sector.
• Enterprise Data Platform (EDP) Ownership
• Own end-to-end architecture, operations, and continuous improvement of the EDP built on Databricks and Microsoft Azure.
• Drive data lake and lakehouse design, data ingestion pipelines, and real-time and batch processing frameworks.
• Ensure platform scalability, security, and cost efficiency while meeting SLAs for enterprise reporting and analytics consumers.
• Power BI Analytics & Self-Service BI
• Lead the enterprise Power BI program, establishing standards, governance, and a center of excellence model for self-service analytics.
• Drive adoption of Power BI across business units; partner with functional leaders to build decision-grade dashboards and KPI reporting.
• Establish certified datasets, report governance, and row-level security best practices.
• AI/ML & Intelligent Automation
• Lead delivery of AI/ML initiatives including predictive analytics, demand forecasting, agentic AI, NLP, and intelligent automation solutions.
• Manage the AI engineering pipeline leveraging Azure AI Foundry, ensuring responsible AI practices, model governance, and MLOps.
• Identify and prioritize high-ROI AI use cases in partnership with business leaders; drive proof of concept through production deployment.
• Evaluate and integrate large language models (LLMs) and generative AI capabilities into enterprise workflows.
• Data Analytics & AI Center of Excellence (CoE)
• Build, lead, and continuously mature the Data Analytics & AI CoE, including governance frameworks, best practices, reusable assets, and community of practice.
• Establish and enforce enterprise standards for data modeling, analytics development, and AI/ML model lifecycle management.
• Business Stakeholder Collaboration & Influence
• Develop and sustain deep, trust-based relationships with senior business stakeholders across finance, supply chain, manufacturing operations, sales, and HR.
• Translate complex analytical and AI capabilities into business value narratives; influence C-suite and VP-level leaders.
• Act as the primary analytics business partner for key enterprise programs including Oracle Fusion ERP, Profisee MDM, and Microsoft technology platforms (Dynamics, myrheem, and other).
• Data Governance, MDM & Data Quality
• Own the enterprise data governance strategy including policies, stewardship, lineage, and data quality frameworks.
• Lead integration and ongoing operations of Profisee MDM, ensuring master data accuracy across Oracle Fusion, Databricks, and downstream systems.
• Drive data quality KPIs and remediation workflows in partnership with business data stewards.
• Team Leadership & Talent Development
• Recruit, develop, and retain a high-performing team of approximately 8–10 data engineers, analytics engineers, BI developers, and data scientists.
• Establish clear roles, career paths, and performance expectations; foster a culture of accountability, innovation, and continuous learning.
• Coach team members in agile delivery, data product thinking, and engineering excellence.
• Budget, Vendor & Partnership Management
• Manage the analytics and AI domain budget, including licensing, cloud infrastructure costs, and professional services.
• Lead vendor relationships and contract negotiations for Databricks, Power BI, Azure AI services, Profisee, and other analytics tooling.
• Evaluate and onboard strategic technology partners to accelerate capability development.
• Oracle Fusion & EBS Data Integration
• Ensure robust data integration between Oracle Fusion (and legacy Oracle EBS), the EDP, and downstream analytics and reporting systems.
• Migrate and centralize reporting and analytics through Fusion Data Intelligence (FDI)
• Partner with the Oracle Fusion program team to define analytics requirements and data architecture for Wave 1 and subsequent rollouts.
• KPI Tracking, Security & Compliance
• Define and track KPIs for platform performance, data quality, BI adoption, and AI value realization.
• Ensure all data and AI systems comply with Rheem's information security policies, data privacy regulations, and audit requirements.
• Emerging Technology Evaluation
• Continuously monitor and assess the analytics and AI technology landscape; present recommendations on emerging tools, platforms, and methodologies.
• Lead structured proof-of-concept engagements with new technology vendors and translate findings into actionable investment recommendations.

Requirements

• 12+ years of progressive experience in data, analytics, and/or AI roles, with at least 5+ years in a director-level leadership position.
• Proven track record leading enterprise data platform programs (data lake, lakehouse, or EDW) at scale in a manufacturing, industrial, HVAC, or building products environment.
• Deep technical expertise with Databricks, Azure Data Services (Data Factory, Synapse, Azure AI Foundry), Power BI, Python, and SQL.
• Demonstrated experience delivering AI/ML and generative AI solutions from concept through production, including MLOps practices.
• Strong experience with data governance, MDM platforms (e.g., Profisee, Informatica, or equivalent), and data quality management.
• Experience integrating data from Oracle ERP systems (Fusion or EBS) into enterprise data platforms.
• Exceptional stakeholder engagement skills , able to influence without authority and translate technical capabilities into business outcomes.
• High accountability and ownership mindset; proven ability to deliver in a fast-paced, matrixed organization.
• Experience managing and developing multi-disciplinary data and analytics teams.
• Strong budget management and vendor negotiation capabilities.
• Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or related field; Master's degree preferred.
• Ability to travel up to 25% as required.
• Experience with Oracle Fusion ERP data architecture and analytics integration in a manufacturing environment.
• Relevant certifications such as Databricks Certified Data Engineer/Associate, Microsoft Certified: Azure Data Engineer Associate, or DP-600 (Fabric Analytics Engineer).
• Experience building or maturing a Data Analytics & AI Center of Excellence (CoE).
• Familiarity with LeanIX enterprise architecture tooling or similar EA platforms.
• Exposure to global manufacturing operations spanning the US, Canada, and international markets.
• Experience with enterprise integration platforms.
• Demonstrated change management experience leading analytics and AI adoption programs.
• Background in decarbonization, sustainability analytics, or ESG reporting is a plus.
• Experience with agentic AI frameworks, prompt engineering, and responsible AI governance.

Skills

Required

• Databricks
• Power BI
• Python
• SQL
• Data governance
• Data quality management
• Oracle ERP systems (Fusion or EBS)
• Stakeholder engagement
• Influence without authority
• Budget management
• Vendor negotiation
• Team leadership

Preferred

• Oracle Fusion ERP data architecture
• DP-600 (Fabric Analytics Engineer)
• LeanIX enterprise architecture tooling
• Enterprise integration platforms
• Change management
• Agentic AI frameworks
• Prompt engineering
• Responsible AI governance