Railway Data Engineer & Power BI Specialist

SMRT Corporation; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

SMRT Corporation is seeking a data-focused engineer to advance our data-driven maintenance strategy. You will own existing data solutions, improve reliability and performance, and build new data pipelines and dashboards that empower engineers to act swiftly and confidently.

You will contribute to preventive, condition-based, and predictive maintenance, and design simulations and what-if analyses to optimize spares provisioning and workforce planning.

Qualifications

• Degree in Engineering, Computer Science, Information Systems, or equivalent professional experience.
• 3–6 years of hands-on data engineering or analytics engineering experience with production pipelines.
• Experience in maintenance, rail, asset-intensive, or industrial operations preferred.

Responsibilities

• Collaborate with Data Engineers and Cloud Solutions Architect to implement data pipelines.
• Develop ETL scripts to ensure high data quality.
• Support fault diagnostics and reliability trend analysis with Railway Infrastructure Engineers.
• Enhance maintenance dashboards to present timely defect status to Maintenance Engineers.
• Scout for maintenance and green technologies to support sustainability goals.
• Assist ESG initiatives and sustainability projects and align with compliance goals.
• Manage ESG project activities and report on performance metrics.
• Translate operational feedback into actionable improvements.

Skills

Excel

Python

Power BI

Azure Data Engineer cert

Azure Data Scientist cert

Education

Bachelor's degree in Engineering / CS / IS or equivalent

Job description

SMRT Corporation is seeking a data-focused engineer to advance our data-driven maintenance strategy. You will own existing data solutions, improve reliability and performance, and build new data pipelines and dashboards that empower engineers to act swiftly and confidently.

You will contribute to preventive, condition-based, and predictive maintenance, and design simulations and what-if analyses to optimize spares provisioning and workforce planning.