Sr. Manager – Digital Product & Reliability

Carpenter Technology Corporation•Raleigh, NC

About The Position

Carpenter Technology Corporation is a leading producer and distributor of premium specialty alloys, including titanium alloys, nickel and cobalt based superalloys, stainless steels, alloy steels and tool steels. Carpenter Technology’s high-performance materials and advanced process solutions are an integral part of critical applications used within the aerospace, transportation, medical and energy markets, among other markets. Building on its history of innovation, Carpenter Technology’s wrought and powder technology capabilities support a range of next-generation products and manufacturing techniques, including novel magnetic materials and additive manufacturing. The Sr. Manager – Digital Product & Reliability leads the strategy, architecture, and scaling of digital capabilities that drive asset reliability, maintenance effectiveness, and operational uptime across manufacturing operations. This role combines product leadership, digital solution architecture, and data/AI enablement to transform maintenance and reliability from reactive execution to predictive and data-driven operations. Operating at the intersection of Maintenance, Reliability Engineering, Operations, Supply Chain, and Digital/Data teams, this role is accountable for translating reliability and asset management practices into scalable digital products, governed data foundations, and intelligent decision-support capabilities. The role also provides leadership in evaluating and applying modern digital, AI, and automation technologies, ensuring solutions are practical, scalable, and aligned to enterprise architecture and business value.

Requirements

Bachelor’s degree in Engineering, Technology, or a related field required
10+ years of experience in digital, manufacturing, maintenance, or reliability environments
3+ years of experience in a Digital Product Manager or Product Owner role
Strong knowledge of RCM methodologies, FMEA, and preventive maintenance practices
Experience with reliability technologies such as SCADA, vibration monitoring, thermography, or route-based monitoring
Strong understanding of maintenance workflows and asset performance drivers
Hands-on experience applying structured problem-solving and root cause analysis methods
Proven ability to deliver digital solutions in asset-intensive industrial environments
Experience translating business requirements into scalable digital products
Strong ability to manage competing priorities and adapt in dynamic environments
Experience evaluating and implementing vendor or platform-based solutions
Experience transforming raw data into meaningful business insights
Strong understanding of industrial data ecosystems and analytics platforms
Exposure to predictive maintenance, machine learning, or advanced analytics
Experience working with CMMS / EAM systems
Exposure to SAP PM, including: Maintenance plans, equipment, and work order processes
Process design, configuration, and system enhancements
Testing, user training, and post-implementation support
Strong awareness of modern digital, AI, and automation technologies
Ability to evaluate and recommend fit-for-purpose technology solutions
Understanding of system integration, data flows, and scalable architecture principles

Nice To Haves

Professional certifications such as PMP or equivalent are a plus
Experience or training in AI/ML technologies is a plus

Responsibilities

Own the digital product vision, roadmap, and backlog for maintenance and reliability capabilities
Translate reliability strategies into clearly defined digital use cases and scalable solutions
Design modular, reusable capabilities that can be deployed across plants and asset classes
Ensure alignment with enterprise data standards, platform architecture, and interoperability requirements
Balance near-term value delivery with long-term scalability, standardization, and AI readiness
Stay current with emerging digital, AI, and automation technologies and assess applicability to manufacturing reliability use cases
Evaluate and recommend technologies based on business needs, scalability, and return on investment
Define scalable solution patterns in collaboration with architecture and engineering teams
Ensure interoperability across enterprise systems including EAM/CMMS, SAP, IoT platforms, data platforms, and analytics tools
Drive reuse of components, services, and data models to avoid siloed or fragmented solutions
Guide build vs. buy decisions and vendor solution selection
Ensure digital solutions are designed with data, analytics, and AI consumption in mind
Digitally enable key reliability practices, including asset criticality, RCM, FMEA, PM optimization, and defect elimination
Ensure processes are standardized, structured, and digitized across sites
Apply structured problem-solving techniques and data-driven analysis to improve asset performance
Embed decision-support capabilities into maintenance workflows
Lead digital enablement of end-to-end work management processes
Drive consistency in work identification, planning, scheduling, execution, and closure
Ensure high-quality, standardized data capture across maintenance activities
Establish closed-loop feedback mechanisms to improve execution quality and data reliability
Lead digital enablement of MRO inventory and spare parts management
Improve master data quality and linkage between assets, maintenance plans, and materials
Enable risk-based spare parts strategies aligned to asset criticality
Support inventory optimization, service-level improvement, and cost control
Collaborate with Supply Chain teams to ensure alignment between maintenance and materials planning
Own reliability-focused data products including asset master, maintenance history, condition monitoring, and failure analytics
Define and enforce standardized data models, naming conventions, and governance practices
Enable federated data ownership while maintaining enterprise-wide consistency and quality
Ensure data products are discoverable, reusable, secure, and fit for reporting, analytics, and AI use
Drive transformation of raw operational data into actionable business insights
Education and/or Training: Bachelor’s degree in Engineering, Technology, or a related field required
Professional certifications such as PMP or equivalent are a plus
10+ years of experience in digital, manufacturing, maintenance, or reliability environments
3+ years of experience in a Digital Product Manager or Product Owner role
Strong knowledge of RCM methodologies, FMEA, and preventive maintenance practices
Experience with reliability technologies such as SCADA, vibration monitoring, thermography, or route-based monitoring
Strong understanding of maintenance workflows and asset performance drivers
Hands-on experience applying structured problem-solving and root cause analysis methods
Proven ability to deliver digital solutions in asset-intensive industrial environments
Experience translating business requirements into scalable digital products
Strong ability to manage competing priorities and adapt in dynamic environments
Experience evaluating and implementing vendor or platform-based solutions
Experience transforming raw data into meaningful business insights
Strong understanding of industrial data ecosystems and analytics platforms
Exposure to predictive maintenance, machine learning, or advanced analytics
Experience or training in AI/ML technologies is a plus
Experience working with CMMS / EAM systems
Exposure to SAP PM, including: Maintenance plans, equipment, and work order processes
Process design, configuration, and system enhancements
Testing, user training, and post-implementation support
Strong awareness of modern digital, AI, and automation technologies
Ability to evaluate and recommend fit-for-purpose technology solutions
Understanding of system integration, data flows, and scalable architecture principles