DCN Process Engineer

Come join us at SLB New Energy & Industrial and be part of a global company driving energy innovation for a balanced planet

SLB New Energy & Industrial (NEI) is a division of SLB; our portfolio includes ventures in carbon capture and sequestration, geothermal power, energy storage, sustainable battery-grade lithium, hydrogen and Data center infrastructure solutions. To know more about NEI please visit https://www.slb.com/about/driving-energy-innovation/scaling-new-energy-systems

Our Data Center infrastructure solutions business provides Innovative and cost-effective solutions that enable building faster, smarter and more resilient data centers. Our modular infrastructure solutions scale AI and cloud computing capacity while minimizing capital risk and deployment delays. From design and supply chain to commissioning and operations, by standardizing components and relocating labor to controlled offsite environments, we help reduce costs, improve lead times, and lower construction risk while ensuring quality and global repeatability. To know more about our Data Centers Infrastructure solutions please visit https://www.slb.com/products-and-services/scaling-new-energy-systems/data-center-infrastructure-solutions

SLB is seeking a Process Engineer who will be responsible for developing, implementing, and optimizing manufacturing and warehouse processes that enable safe, efficient, and scalable production operations. This role works closely with Manufacturing, Quality, Engineering, Supply Chain, and Operations teams to improve productivity, quality, and product flow while supporting new product introductions and continuous improvement initiatives.

The successful candidate will leverage expertise in process design, validation, statistical analysis, and operational excellence to ensure robust and repeatable manufacturing processes. As a subject matter expert in process development and optimization, the Process Engineer will play a critical role in driving operational performance and supporting the production of world-class data center infrastructure solutions.

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This position is based on site in Calgary, Alberta.

Roles and Responsibilities:

• Develop, implement, and optimize manufacturing and warehouse processes to improve safety, quality, productivity, and operational efficiency.
• Analyze material flow, facility layout, and production workflows to improve throughput, reduce waste, and support scalable operations.
• Conduct capacity analyses, bottleneck assessments, and simulation studies to optimize manufacturing processes and material handling systems.
• Lead process characterization, validation, and capability studies utilizing methodologies such as DOE, SPC, PFMEA, and process capability analysis.
• Analyze process performance data to identify trends, determine root causes of variation, and implement corrective and preventive actions.
• Specify, evaluate, commission, and validate manufacturing equipment, tooling, fixtures, automation systems, and warehouse technologies.
• Develop and maintain process documentation, including process flow diagrams, value stream maps (VSM), work instructions, standard operating procedures, control plans, and visual management tools.
• Partner with Manufacturing, Quality, Maintenance, Supply Chain, and Production teams to resolve process-related issues and improve operational performance.
• Support New Product Introduction (NPI) activities by developing scalable manufacturing processes, identifying risks, and ensuring production readiness.
• Lead process risk assessments and implement mitigation strategies to ensure safety, quality, regulatory compliance, and process robustness.
• Establish, monitor, and report key process performance indicators, including cycle time, throughput, yield, OEE, inventory flow, and scrap/rework rates.
• Drive Lean Manufacturing and Continuous Improvement initiatives focused on waste reduction, efficiency improvements, and cost optimization.
• Provide technical leadership, training, and guidance to production personnel regarding process changes, standards, and best practices.
• Support digital manufacturing initiatives through data collection, reporting, automation, and process visualization tools.

Qualifications & Experience:

• Bachelor's degree in Industrial Engineering, Manufacturing Engineering, Process Engineering, Mechanical Engineering, or a related technical discipline.
• Minimum 5 years of experience in process engineering, manufacturing engineering, industrial engineering, or operations improvement within a manufacturing environment.
• Demonstrated experience developing and optimizing manufacturing and/or warehouse processes in a production environment.
• Hands-on experience with process mapping, workflow design, time studies, statistical analysis, and process validation methodologies.
• Experience commissioning, validating, troubleshooting, and improving manufacturing equipment, automation systems, or production technologies.
• Proven ability to analyze operational data and implement sustainable improvements that improve productivity, quality, safety, or cost performance.
• Experience supporting New Product Introduction (NPI) and manufacturing readiness activities.
• Strong understanding of manufacturing systems, material flow, inventory control, and operational excellence principles.

Preferred Skills:

• Strong analytical and problem-solving skills, including experience with statistical software such as Minitab, JMP, or equivalent tools.
• Experience applying Lean Manufacturing and Continuous Improvement methodologies; Lean Six Sigma Green Belt or Black Belt certification preferred.
• Proficiency in PFMEA, Control Plans, Process Flow Diagrams, Standardized Work, and Statistical Process Control (SPC).
• Experience with facility layout design, value stream mapping, warehouse optimization, and material handling systems.
• Proficiency with CAD software for process layouts, workstation design, and manufacturing improvements.
• Experience with ERP, MES, or manufacturing reporting systems, including SAP.
• Experience utilizing Microsoft Power BI, Power Apps, or similar digital tools to improve visibility, reporting, and process automation.
• Advanced Microsoft Excel skills, including data analysis, VBA, Macros, and reporting automation.
• Strong communication and stakeholder management skills, with the ability to collaborate effectively across Engineering, Operations, Quality, Supply Chain, and Leadership teams.
• Experience in assembly-based manufacturing environments involving mechanical, electrical, or modular products is preferred.
• Experience supporting high-growth, startup, or rapidly scaling manufacturing operations is considered an asset.

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By applying for this position, I hereby expressly acknowledge and consent to the following:

I consent to the collection, storage, transfer and processing of personal data strictly in relation with and for the purpose of the recruitment procedure and onboarding (if applicable). I acknowledge that my data will be accessible by SLB’s talent acquisition and onboarding teams, who are located worldwide.

I further acknowledge that I have the right to access to such data and to correct any errors, which may be contained therein. I understand this can be done by contacting Schlumberger Canada Limited’s (“SLB Canada”) privacy officer. The SLB Canada privacy officer may be contacted by calling 403-509-4000.

I agree that any misrepresentation of information in the application process, or during onboarding, if applicable (including but not limited to the this application, resume, transcripts, and Driver's Abstract or during the course of an interview) is an act of dishonesty and may be grounds for halting the application and/or onboarding process or for termination with cause (if applicable).

I understand that SLB may disclose my personal information to third party providers as maybe be required to carry out the application and onboarding (where applicable) process. I further agree that SLB may obtain personal information about me from these third parties, including but not limited to, employment history, academic training including verification of any diplomas, degrees or professional accreditations, driver’s abstract and records of criminal convictions for which a pardon/record suspension was not granted in accordance with the Criminal Records Act, RSC 1985, c C47.

I understand that the retention period for the data contained in my application form is 3 years from the date of application.