Lead, Engineering Data & Intelligence Strategy

Trane Technologies

. Develop and advance Engineering's data and intelligence strategy aligned with Engineering IQ, business objectives, and enterprise data and technology standards .

Posted 10/30/2026full-timeUnited StatesSenior💰 $113,600 - $235,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and advancing data and analytics strategies, governance frameworks, and scalable data solutions. Proven ability to lead cross-functional initiatives, drive organizational change, and foster partnerships to enhance data quality and accessibility.

Highest-signal resume keywords

Data Governance FrameworksData Management PrinciplesAnalytics Strategy DevelopmentCross-Functional LeadershipBusiness Intelligence

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureData AnalyticsData Quality ManagementData StewardshipAI CapabilitiesDigital TransformationMaster Data ManagementSemantic ModelsTaxonomiesOntologies

Soft Skills

Excellent CommunicationProblem-SolvingStrategic PlanningCollaborationInfluence

Tools & Technologies

Cloud Data PlatformsPLM SystemsERP SystemsKnowledge Repository Systems

Industry Keywords

EngineeringManufacturingIndustrial EnvironmentsData ScienceBusiness Strategy

Tech Stack

Tools & technologies

CloudERP

About the role

Key responsibilities & impact

Develop and advance Engineering's data and intelligence strategy aligned with Engineering IQ, business objectives, and enterprise data and technology standards
Establish roadmaps and priorities to improve accessibility, quality, governance, and reuse of critical engineering information
Partner with Engineering leaders and subject matter experts to identify business needs, define information requirements, and prioritize analytics, data science, and AI opportunities
Establish and guide an Engineering data governance and stewardship operating model, including ownership, accountability, decision-making, and escalation processes
Define and adopt common data definitions, classification standards, quality expectations, and ownership frameworks with data owners, stewards, and technical architects
Guide engineering taxonomies, ontologies, and semantic standards supporting knowledge graphs, digital-thread capabilities, and AI initiatives
Collaborate with data architects, engineers, and IT teams to establish scalable, governed data foundations across PLM, ERP, laboratory, and knowledge repository systems
Identify opportunities for automation and AI-assisted data engineering, classification, and stewardship
Facilitate cross-functional alignment and lead organizational change to promote common standards, processes, and data-driven ways of working
Partner with technical teams to address data quality issues, integration challenges, and barriers to information accessibility
Establish measures of business value, adoption, data quality, and operational efficiency to evaluate progress and guide continuous improvement
Build partnerships across Engineering, business functions, and enterprise technology teams to promote reusable capabilities, shared accountability, and sustainable solutions

Requirements

What you’ll need

Bachelor's degree in engineering, data science, information systems, business, analytics, or a related field, or equivalent practical experience
At least eight years of experience in data and analytics, business strategy, technology, or digital transformation, including experience leading cross-functional initiatives
Experience developing data and analytics strategies, roadmaps, governance frameworks, or operating models
Strong understanding of data management, analytics, data architecture principles, and organizational capabilities for scalable data solutions
Experience translating business objectives into data, analytics, and technology priorities that deliver measurable value
Ability to lead through influence, build cross-functional partnerships, and align stakeholders in a complex, matrixed organization
Experience driving organizational change, stakeholder engagement, and adoption of new technologies or ways of working
Strong understanding of business intelligence, advanced analytics, data science, and emerging AI capabilities
Excellent communication, facilitation, problem-solving, and strategic planning skills
Ability to work independently, navigate ambiguity, and drive progress through collaboration and influence
Experience in manufacturing, engineering, or industrial environments is preferred
Familiarity with master data management, data governance, data quality, and stewardship practices is preferred
Familiarity with cloud data platforms, semantic models, taxonomies, ontologies, or knowledge graphs is preferred
Advanced degree in Data Science, Business Administration, Engineering, or a related field is preferred

Benefits

Comp & perks

Health insurance for employees and family
Holistic wellness programs with generous incentives
Fertility coverage
Adoption/surrogacy assistance
Up to 15 vacation days
Paid holidays
Sick leave
Volunteer leave
Parental leave
401K match
Educational and training opportunities through company programs
Tuition assistance
Student debt support