Engineering Data & Intelligence Strategy Architect

Trane Technologies plc; Davidson (NC); Presencial; USD 114.000 - 236.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401K match

Paid time off

Descripción de la vacante

Trane Technologies is seeking an Engineering Data & Intelligence Strategy Architect to advance data strategy, governance, and adoption for Engineering IQ and AI-driven workflows. The role connects engineering priorities with data foundations, guiding governance and scalable solutions across PLM, ERP, and laboratory data.

The senior contributor will drive taxonomies, ontologies, and semantic standards, partnering with data owners and IT to enable trusted, accessible information and measurable

Formación

• Bachelor’s degree or equivalent practical experience in a related field.
• Eight+ years of data/analytics, strategy, technology, or digital transformation experience.
• Experience building data governance, roadmaps, and operating models.
• Understanding of data management, architecture, and governance for scalable solutions.
• Ability to translate business objectives into data/tech priorities with measurable value.
• Strong influencing, cross-functional partnership, and stakeholder alignment skills.
• Experience driving organizational change and adoption of new tech/workflows.
• Knowledge of BI, analytics, data science, and AI capabilities.
• Excellent communication, facilitation, problem-solving, and planning skills.
• Experience in manufacturing/engineering environments preferred.
• Familiarity with master data management and data quality practices preferred.
• Familiarity with cloud data platforms and knowledge graphs preferred.
• Advanced degree preferred in related fields.

Responsabilidades

• Develop and advance Engineering data and intelligence strategy aligned with Engineering IQ and enterprise standards.
• Establish roadmaps to improve accessibility, quality, governance, and reuse of critical engineering information.
• Partner with leaders to identify needs, define information requirements, and prioritise analytics, data science, and AI opportunities.
• Create and guide an Engineering data governance and stewardship operating model with clear ownership and escalation.
• Define common data definitions, classifications, quality expectations, and ownership frameworks.
• Guide development of taxonomies, ontologies, and semantic standards for knowledge graphs and digital-thread initiatives.
• Collaborate with architects, engineers, and IT to build scalable, governed data foundations across PLM, ERP, labs, and knowledge repos.
• Identify opportunities to leverage automation and AI-enabled data engineering to accelerate delivery and reduce costs.
• Lead cross-functional alignment and drive adoption of standards and data-driven ways of working.
• Address data quality, integration challenges, and barriers to information accessibility with technical teams.
• Establish measures of value, adoption, and efficiency to guide continuous improvement.
• Build partnerships across Engineering, business functions, and enterprise tech teams for reusable capabilities.

Conocimientos

Data strategy

Cross-functional leadership

Data governance

Analytics concepts

Communication

Independent work

Ambiguity navigation

Manufacturing/engineering experience

Strategic planning

Educación

Bachelor’s degree in engineering, data science, information systems, business, analytics, or related field

Advanced degree preferred (Data Science / Engineering / MBA)

Herramientas

Cloud platforms

Semantic models

Taxonomies & ontologies

Knowledge graphs

Descripción del empleo

Trane Technologies is seeking an Engineering Data & Intelligence Strategy Architect to advance data strategy, governance, and adoption for Engineering IQ and AI-driven workflows. The role connects engineering priorities with data foundations, guiding governance and scalable solutions across PLM, ERP, and laboratory data.

The senior contributor will drive taxonomies, ontologies, and semantic standards, partnering with data owners and IT to enable trusted, accessible information and measurable