Condition Monitoring Engineer
AssetWatch, Inc.
Full_time•Canada
📍 Job Overview
- Job Title: Condition Monitoring Engineer
- Company: AssetWatch, Inc.
- Location: Ontario, Canada
- Job Type: On-site
- Category: Predictive Maintenance & Condition Monitoring
- Date Posted: July 30, 2025
- Experience Level: Mid-Senior level (5-10 years)
- Remote Status: On-site (Ontario, Canada only)
🚀 Role Summary
- Key Responsibilities: Collect and analyze vibration and temperature data, evaluate machinery health, develop software models, and provide actionable information to clients.
- Key Skills: Vibration data collection and analysis, software modeling, electro-mechanical fundamentals, mechanical background, and strong communication skills.
💻 Primary Responsibilities
🔬 Data Collection & Analysis
- Data Collection: Collect vibration and temperature data at client sites using FFT analyzers and other predictive/preventative maintenance software.
- Data Analysis: Analyze collected data, customize processing, and determine maintenance needs.
- Software Modeling: Develop and maintain software models and programs to expand the vibration data analysis library and improve data processing capabilities.
🛠 Machinery Health Evaluation
- Machinery Health Assessment: Evaluate machinery health and condition through detailed analysis of vibration data.
- Alarm Level Setting: Set appropriate alarm levels within analytical tools to alert customers of pending failures.
🛡️ Maintenance & Growth
- Maintenance Recommendations: Provide high-quality, actionable information to clients, recommending maintenance actions based on data analysis.
- Program Expansion: Lead and grow AssetWatch's predictive maintenance (PdM) tool development program, expanding expertise beyond vibration analysis to include ultrasonic analysis and oil/fluid analysis.
- Product Development: Work closely with the product development team to create high-valued hardware and software solutions, and expanded product offerings.
🎓 Skills & Qualifications
📚 Education & Experience
- Education: Relevant engineering degree or equivalent experience.
- Experience: Minimum of five years of relevant experience in vibration data collection and analysis.
🛠 Required Skills
- Data Analysis: Proficiency in vibration data collection, analysis, and software modeling.
- Mechanical Background: Strong understanding of electro-mechanical fundamentals and industrial equipment.
- Communication: Excellent communication and interpersonal skills.
- Certification: Valid ISO Category II, or higher, vibration certification (preferred).
🌟 Preferred Skills
- Programming: Proficiency in programming languages relevant to predictive maintenance software.
- Customer Focus: Demonstrated ability to understand and address customer needs.
- Integrity: Proven integrity, ethical behavior, and responsibility in accomplishing work.
📊 Web Portfolio & Project Requirements
- Portfolio Essentials:
- Case studies demonstrating vibration data collection, analysis, and maintenance recommendations.
- Examples of software models and programs developed to improve data processing capabilities.
- Evidence of machinery health evaluations and alarm level settings.
- Technical Documentation:
- Detailed documentation of data collection methods, analysis techniques, and maintenance recommendations.
- Code comments and version control for software models and programs.
💵 Compensation & Benefits
💰 Salary Range
- Estimate: CAD 90,000 - CAD 120,000 per year (based on experience level and industry standards for predictive maintenance engineers in Ontario, Canada).
🎁 Benefits
- Compensation Package: Competitive compensation package including stock options.
- Work Schedule: Flexible work schedule.
- Benefits: Comprehensive benefits including retirement plan match.
- PTO: Unlimited PTO.
🎯 Team & Company Context
🏢 Company Culture
- Industry: Global manufacturing predictive maintenance.
- Company Size: Small to medium-sized, growing team.
- Founded: Not specified.
- Team Structure: Distributed team working remotely across the United States and Ontario, Canada, with collaboration within core working hours required.
- Development Methodology: Not specified.
📈 Career & Growth Analysis
- Web Technology Career Level: Mid-Senior level predictive maintenance engineer, with opportunities for growth and leadership in the field.
- Reporting Structure: Reporting directly to the company's leadership team, with close collaboration with product development, installation, and customer support teams.
- Technical Impact: Significant technical impact on the company's predictive maintenance offerings and customer satisfaction.
🌐 Work Environment
- Office Type: Remote-first, with on-site requirements for Ontario, Canada-based candidates.
- Office Location(s): Ontario, Canada.
- Workspace Context: Collaborative workspace with a dynamic and growing team, requiring strong communication and interpersonal skills.
- Work Schedule: Flexible work schedule, with unlimited PTO.
📄 Application & Technical Interview Process
📝 Application Process
- Application Submission: Submit your application through the provided link.
- Resume Optimization: Highlight relevant experience and skills, with a focus on vibration data collection, analysis, and software modeling.
- Portfolio Preparation: Prepare a portfolio showcasing case studies, software models, and other relevant projects.
- Company Research: Research AssetWatch's predictive maintenance offerings and customer base.
💼 Interview Process
- Interview Stages: Multiple interview stages, including technical assessments and behavioral interviews.
- Technical Assessment: Demonstrate proficiency in vibration data collection, analysis, and software modeling through hands-on exercises and case studies.
- Behavioral Interview: Discuss problem-solving skills, customer focus, and integrity through behavioral-based questions.
🛠 Technology Stack & Web Infrastructure
- Data Collection Tools: FFT analyzers and predictive/preventative maintenance software.
- Data Analysis Tools: Not specified.
- Software Development: Programming languages relevant to predictive maintenance software.
- Version Control: Not specified.
👥 Team Culture & Values
- Company Values: Customer focus, integrity, and collaboration.
- Collaboration Style: Collaborative workspace with a dynamic and growing team, requiring strong communication and interpersonal skills.
⚡ Challenges & Growth Opportunities
🛠 Technical Challenges
- Data Analysis: Developing and maintaining software models and programs to improve data processing capabilities.
- Machinery Health Evaluation: Evaluating machinery health and condition through detailed analysis of vibration data.
- Product Development: Working closely with the product development team to create high-valued hardware and software solutions.
🌱 Learning & Development Opportunities
- Technical Skill Development: Expanding expertise in machine condition monitoring, beyond vibration analysis, to include ultrasonic analysis and oil/fluid analysis.
- Leadership Development: Opportunities for growth and leadership in the field of predictive maintenance.
💡 Interview Preparation
📝 Technical Questions
- Data Analysis: Questions related to vibration data collection, analysis, and software modeling.
- Machinery Health Evaluation: Questions related to evaluating machinery health and condition through detailed analysis of vibration data.
- Problem-Solving: Behavioral-based questions focusing on problem-solving skills, customer focus, and integrity.
📝 Company & Culture Questions
- Company Knowledge: Questions assessing understanding of AssetWatch's predictive maintenance offerings and customer base.
- Team Fit: Questions evaluating cultural fit and collaboration skills.
📌 Application Steps
- Submit your application through the provided link.
- Optimize your resume, highlighting relevant experience and skills.
- Prepare a portfolio showcasing case studies, software models, and other relevant projects.
- Research AssetWatch's predictive maintenance offerings and customer base.
- Review and practice for the technical assessment and behavioral interviews.
Content Guidelines (IMPORTANT: Do not include this in the output)
Web Technology-Specific Focus:
- Tailor every section specifically to predictive maintenance and condition monitoring roles.
- Include predictive maintenance methodologies, data analysis techniques, and machinery fundamentals.
- Emphasize portfolio requirements, case studies, and software modeling examples.
- Address predictive maintenance team dynamics, cross-functional collaboration with product development and customer support teams.
- Focus on predictive maintenance career progression, technical skill development, and leadership opportunities.
Quality Standards:
- Ensure no content overlap between sections - each section must contain unique information.
- Only include Enhancement Notes when making significant inferences about predictive maintenance processes, data analysis techniques, or team structure.
- Be comprehensive but concise, prioritizing actionable information over descriptive text.
- Strategically distribute predictive maintenance and condition monitoring-related keywords throughout all sections naturally.
- Provide realistic salary ranges based on location, experience level, and predictive maintenance specialization.
Industry Expertise:
- Include specific predictive maintenance and condition monitoring tools, software, and techniques relevant to the role.
- Address predictive maintenance career progression paths and technical leadership opportunities in predictive maintenance teams.
- Provide tactical advice for portfolio development, case studies, and software modeling examples.
- Include predictive maintenance-specific interview preparation and data analysis challenge guidance.
- Emphasize machinery health evaluation, alarm level setting, and customer focus principles.
Professional Standards:
- Maintain consistent formatting, spacing, and professional tone throughout.
- Use predictive maintenance and condition monitoring industry terminology appropriately and accurately.
- Include comprehensive benefits and growth opportunities relevant to predictive maintenance professionals.
- Provide actionable insights that give predictive maintenance candidates a competitive advantage.
- Focus on predictive maintenance team culture, cross-functional collaboration, and customer satisfaction measurement.
Technical Focus & Portfolio Emphasis:
- Emphasize predictive maintenance best practices, data analysis techniques, and machinery fundamentals.
- Include specific portfolio requirements tailored to the predictive maintenance discipline and role level.
- Address data collection methods, analysis techniques, and maintenance recommendations.
- Focus on problem-solving methods, software modeling, and customer impact measurement.
- Include technical presentation skills and stakeholder communication for predictive maintenance projects.
Avoid:
- Generic business jargon not relevant to predictive maintenance or condition monitoring roles.
- Placeholder text or incomplete sections.
- Repetitive content across different sections.
- Non-technical terminology unless relevant to the specific predictive maintenance role.
- Marketing language unrelated to predictive maintenance, condition monitoring, or customer experience.
Application Requirements
Candidates must have a minimum of five years of relevant experience in vibration data collection and analysis, with a strong understanding of electro-mechanical fundamentals. A valid ISO Category II vibration certification is preferred, along with proficiency in Microsoft Office Suite.