Leader, Engineering Data & Intelligence Strategy

Trane Technologies • La Crosse, NC

5d • Hybrid

About The Position

Trane Technologies is seeking an Engineering Data & Intelligence Strategy Architect to advance the strategy, governance, and adoption of engineering data and knowledge capabilities supporting Engineering IQ, advanced analytics, and artificial intelligence. This senior individual contributor role has no direct reports and connects Engineering business priorities with the data foundations, standards, and organizational capabilities needed to make information trusted, accessible, and reusable.

The role works across Engineering, Manufacturing, Procurement, Product Management, Service, and IT to establish strategic priorities, guide data governance and stewardship, and partner with technical specialists on scalable solutions. Relevant engineering data domains include laboratory data, product lifecycle information, parts and materials, engineering documents, product configuration, and supplier data. The position also advances engineering taxonomies, ontologies, knowledge graphs, and semantic capabilities for Engineering IQ, digital-thread initiatives, and AI-driven engineering workflows.

The work arrangement is onsite Monday through Thursday, with the option to choose a work location on Fridays based on work needs. The position is incentive eligible and is not sales commission eligible.

Requirements

• 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.
• Demonstrated experience developing data and analytics strategies, roadmaps, governance frameworks, or operating models.
• Strong understanding of data management, analytics, data architecture principles, and the organizational capabilities required to support 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.

Nice To Haves

• Experience in manufacturing, engineering, or industrial environments.
• Familiarity with master data management, data governance, data quality, and stewardship practices.
• Familiarity with cloud data platforms, semantic models, taxonomies, ontologies, or knowledge graphs.
• Advanced degree in Data Science, Business Administration, Engineering, or a related field.

Responsibilities

• Develop and advance Engineering's data and intelligence strategy, aligning priorities with Engineering IQ, business objectives, and enterprise data and technology standards.
• Establish roadmaps and priorities for improving the 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.
• Partner with data owners, stewards, and technical architects to define and adopt common data definitions, classification standards, quality expectations, and ownership frameworks.
• Guide the development of 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 engineering systems, including PLM, ERP, laboratory, and knowledge repositories.
• Identify opportunities to use automation and AI-assisted data engineering, classification, and stewardship to accelerate delivery and reduce costs.
• Facilitate cross-functional alignment and lead organizational change to promote adoption of common standards, processes, and data-driven ways of working.
• Partner with technical teams to identify and 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.

Benefits

• Health insurance and holistic wellness programs with incentives, available from day one.
• Fertility coverage and adoption/surrogacy assistance.
• Up to 15 vacation days, paid holidays, and sick leave.
• Additional options to support volunteer and parental leave.
• 401(k) matching.
• Educational and training opportunities through company programs.
• Tuition assistance and student debt support.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior