Condition Monitoring Engineer

AssetWatch, Inc.
Full_timeCanada

📍 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

  1. Submit your application through the provided link.
  2. Optimize your resume, highlighting relevant experience and skills.
  3. Prepare a portfolio showcasing case studies, software models, and other relevant projects.
  4. Research AssetWatch's predictive maintenance offerings and customer base.
  5. 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.