Senior/Executive, Ops Analysis & Technology, Singapore

Job description:
Job Purpose
Our railway infrastructure, including tracks, tunnels, and viaducts, undergoes routine inspection and monitoring to ensure the highest standards of safety and reliability. We leverage vast amounts of data from laser measurement systems, photo imaging, IoT sensors, and maintenance records to identify defect trends, drive proactive maintenance, and continuously improve our network.
This role is central to our data-driven maintenance strategy, focusing on
Data Engineering
and
Power BI
to deliver critical insights and decision support for our core operations. You will take ownership of existing data solutions, enhance their reliability and performance, and build new data pipelines and dashboards that empower engineers to act faster and with greater confidence.
Your work will directly influence preventive, condition-based, and predictive maintenance regimes. Furthermore, you will design simulations and what-if analyses to optimize spares provisioning and workforce planning, translating operational feedback into tangible improvements.
Responsibilities
The Engineer will assist the Section Manager for Maintenance Technology Integration, OA&T and is responsible for Working with Data Engineers and Cloud Solutions Architect to implement data pipelines Developing extract-transform-load (ETL) scripts to ensure a high level of data quality Teaming with Railway Infrastructure Engineers to support fault diagnostics, mine insights from reliability trends to support maintenance program review Enhance maintenance dashboards to ensure timely and accurate defect status info for the Maintenance Engineers Scout for maintenance & green technologies. Support the implementation of sustainability projects and initiatives. Collaborate with various teams to ensure the alignment of projects with overall sustainability and compliance goals. Project management of ESG initiatives. Monitor and report on sustainability performance metrics. Qualifications & Work Experience
A degree in Engineering (Mechanical, Electrical, Civil), Computer Science, Information Systems, or equivalent professional experience. 3–6 years of hands-on experience
in data engineering or analytics engineering, with proven ownership of production pipelines and BI models. Prior experience in maintenance, rail, asset-intensive, or other industrial operations is strongly preferred. Skills
Proficient in Excel Proficient in Python and its data science packages Proficient in Power BI Having Microsoft Azure Data Engineer certification & Microsoft Azure Data Scientist certification will be a bonus