Infrastructure Predictive Maintenance Development Senior Engineer

Etihad Rail Operating Companies; Al Fayah; On-site; AED 360,000 - 600,000; Full time

Job summary

Etihad Rail Operating Companies seeks an Infrastructure Predictive Maintenance Development Senior Engineer to lead development of predictive, condition-based and risk-based maintenance strategies for critical railway assets.

You will apply asset analytics, degradation trends and residual-life modelling to predict deterioration and optimise interventions, improving reliability, availability and safety while reducing lifecycle costs.

Qualifications

• Bachelor’s degree in Engineering or related field.
• Professional engineering membership or equivalent accreditation is preferred.
• Certification in reliability engineering, condition monitoring, asset management or predictive maintenance is advantageous.

Responsibilities

• Develop predictive maintenance strategies for performance-critical assets.
• Identify assets and systems where predictive maintenance improves reliability and maintenance cost efficiency.
• Define predictive maintenance requirements based on asset criticality, failure modes, and lifecycle risk.
• Develop interventions to transition from time-based to predictive/condition-based maintenance.
• Establish methodologies to evaluate the value of predictive maintenance and improve strategies.

Skills

Analytical Thinking

Data-Driven Decision Making

Critical Thinking & Technical Judement

Education

Bachelor's degree in Engineering

Professional engineering membership

Certifications in reliability/condition monitoring

Tools

Condition-monitoring systems

Analytics platforms

Job description

The Infrastructure Predictive Maintenance Development Senior Engineer is responsible for developing and enhancing predictive, condition-based and risk-based maintenance strategies for key performance-critical and safety-critical railway infrastructure assets.

The role applies asset analytics, advanced data analysis, condition monitoring, asset health indices, degradation trends and residual-life modelling to predict asset deterioration and optimise maintenance interventions. The position aims to improve asset reliability, availability and safety while reducing lifecycle maintenance costs and creating measurable business value through predictive maintenance.

The role also supports the implementation of new predictive maintenance technologies and analytical tools and provides technical input into investment planning, lifecycle strategies and scenario development across infrastructure asset classes.

Roles and Responsibility

• Develop predictive maintenance strategies, methodologies and tactics for performance-critical and safety-critical railway infrastructure assets.
• Identify assets and systems where predictive maintenance can improve reliability, availability, safety, asset life and maintenance cost efficiency.
• Define predictive maintenance requirements based on asset criticality, failure modes, condition, operational impact and lifecycle risk.
• Develop intervention approaches that transition appropriate assets from time-based maintenance toward predictive and condition-based maintenance.
• Establish methodologies to evaluate the effectiveness and business value of predictive maintenance interventions and continuously improve strategies based on performance and emerging technologies.
• Apply advanced asset analytics to identify trends, patterns, anomalies, deterioration and emerging risks across infrastructure assets.
• Analyze historical and real-time condition, inspection, failure, maintenance and operational data to understand asset behaviour and degradation.
• Apply statistical techniques, trend analysis and other analytical methodologies to identify correlations, predict potential failures and support maintenance and lifecycle decisions.
• Translate complex asset analytics and predictive findings into practical engineering recommendations and maintenance interventions.
• Develop and enhance condition-based and risk-based maintenance strategies using asset condition, monitoring, performance and criticality information.
• Establish condition indicators, intervention thresholds and risk-based methodologies for prioritizing maintenance and engineering actions.
• Evaluate existing preventive maintenance tasks and inspection frequencies to identify opportunities for predictive or condition-based optimization while maintaining safety requirements.
• Develop asset health indices, parameters, scoring methodologies and deterioration indicators to provide consistent assessment of asset condition and performance.
• Develop, validate and maintain residual-life models using asset condition, age, performance, failure history, maintenance information and operational data.
• Identify assets approaching critical condition or end-of-life and provide early visibility of maintenance, refurbishment or renewal requirements.
• Identify, evaluate and support implementation of predictive maintenance tools and technologies, including sensors, condition-monitoring systems, diagnostic solutions and analytics platforms.
• Define technical and functional requirements and support trials, pilots, testing, validation and implementation of new predictive maintenance technologies.
• Work with Engineering, Maintenance, IT/Data, OEMs and technology providers to integrate predictive maintenance capabilities into existing asset-management and maintenance processes.
• Develop dashboards and visualization tools to communicate asset condition, health, degradation trends, predicted failures and emerging risks.
• Identify opportunities to optimize maintenance activities and quantify benefits from predictive maintenance, including avoided failures, reduced maintenance effort, improved availability and extended asset life.
• Support business cases for predictive maintenance initiatives and technology investments, tracking realized performance improvements and value creation.
• Provide predictive insights and asset analytics to support lifecycle strategies, medium- and long-term maintenance planning, renewal prioritization and whole-life cost decisions.
• Define predictive-maintenance data requirements, identify data-quality gaps and support integration and validation of asset, condition, failure and maintenance information.
• Establish and monitor KPIs for predictive maintenance effectiveness, model accuracy and asset-performance improvement, incorporating lessons learned into continuous improvement.
• Collaborate with Asset Management, Engineering, Maintenance, Operations, Lifecycle Planning, IT/Data and external specialists to embed predictive maintenance and asset analytics capability across the organization.

Desirable qualifications, skills and experience

Academic Qualifications:

• Bachelor’s degree in Engineering, preferably Electrical, Electronic, Mechanical, Civil, Railway, Mechatronics or another relevant engineering discipline.
• Professional engineering membership or equivalent accreditation is preferred.
• Relevant certification in reliability engineering, condition monitoring, asset management, data analytics or predictive maintenance would be advantageous.

Experience:

• 8+ years of experience in related field.
• Significant engineering experience within railway, metro, heavy rail or another asset-intensive and safety-critical environment.
• Experience in predictive, condition-based, reliability-centred or risk-based maintenance.
• Practical experience in infrastructure asset condition and performance analysis.
• Experience analyzing asset condition, failure, maintenance and operational data.
• Demonstrated experience applying statistical, trend and advanced analytical techniques to engineering or asset-management problems.
• Experience developing asset health indices, degradation models, residual-life models or equivalent asset-performance methodologies.
• Experience with condition-monitoring systems and technologies.
• Experience supporting maintenance optimization and reliability-improvement initiatives.
• Experience evaluating or implementing predictive maintenance and asset-analytics tools.
• Experience supporting asset lifecycle, investment or renewal planning.
• Knowledge of railway infrastructure assets including track, signalling, telecommunications and civil infrastructure would be advantageous.
• Experience with ISO 55000-aligned asset management environments would be advantageous.

Other Skills:

• Analytical Thinking & Problem Solving
• Data-Driven Decision Making
• Critical Thinking & Technical Judgement