[LTA-RAOM] MGR / SNR / EXEC ENGINEER (DATA ANALYTICS & APPLICATIONS)

Government Technology Agency (GovTech); Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Land Transport Authority is seeking a Data Scientist / Data Analytics Engineer for Asset Management (Data & Analytics). You will design and build data pipelines, transform asset data, and develop analytics solutions to drive asset management insights for rail networks.

You will work with diverse teams including LTA, rail operators, and system manufacturers to review submissions, test solutions, and implement data engineering/analytics projects that support asset performance and decision-making.

Qualifications

• Design, develop, and maintain data pipelines for asset data.
• Ensure data quality, integrity, and accessible data for analytics.
• Translate stakeholders' data needs into technical specs for engineering/analytics.
• Perform data analysis to uncover trends informing asset management.
• Build data models and analytics frameworks aligned with business goals.

Responsibilities

• Design, develop, and maintain data pipelines to collect, process, and transform asset-related data from various sources for both engineering and analytical purposes.
• Ensure data integrity, quality, and accessibility by implementing best practices in data engineering and management.
• Collaborate with stakeholders to understand their data requirements and translate them into technical specifications for both data engineering and analytics projects.
• Conduct data analysis to identify trends, patterns, and insights that inform asset management practices and decision-making.
• Develop and implement data models and analytics frameworks that support business objectives and enhance asset performance.
• Create and maintain dashboards and visualizations that effectively communicate asset performance metrics and analytics findings to stakeholders.
• Implement and manage data within the organisation's storage solutions (e.g., databases, data lakes) to facilitate efficient data retrieval, access and analysis.
• Work with cross-functional teams to prioritize and implement analytics-related user stories, ensuring timely delivery of data-driven insights.
• Document data engineering processes, data flows, and analytics workflows to support knowledge sharing and onboarding.
• Stay current with industry trends, tools, and best practices in data engineering and analytics to continuously improve processes and solutions.

Skills

Data engineering

Data analytics

Python

SQL

ETL tools

Tableau

Power BI

ML models

Data modelling

Education

Bachelor's degree in Data Science/Computer Science/Engineering

Relevant experience in data analytics

Tools

Python

SQL

ETL tools

Tableau

Power BI

LLMs

Job description

[What the role is] DATA SCIENTIST / DATA ANALYTICS ENGINEER (ASSET MANAGEMENT (DATA & ANALYTICS)) [What you will be working on] You will be part of the Asset Management team focusing on data engineering and data analytics to support asset management use cases for the rail network. You will be responsible for designing and building data pipelines to prepare and optimize asset-related data for analytical applications while also involved as part of the implementation team to develop analytics solutions to drive asset management insights and enhance decision-making. You will work closely with teams from different disciplines within LTA, rail operators, system manufacturers on the data of the rail assets and on the rail asset management business use cases. You may also be required to review technical submissions and participate in the testing and commissioning of the data engineering/analytical decision support solutions.

As part of the shortlisting process for the role, you may be required to complete a medical declaration and / or undergo further assessment.

The Singapore Public Service plays a key role in the economic growth, progress and stability of Singapore by formulating and implementing government policies, as well as providing key public services. Whether you are a fresh graduate joining the workforce or an experienced professional, the Singapore Public Service offers a great variety of job opportunities for you. The work in the Public Service can be broadly categorised into the following sectors: Economic, Social, Security & External Relations, and Administration & Corporate Development. Be part of the team that shapes the future of Singapore.

Key Responsibilities

• Design, develop, and maintain data pipelines to collect, process, and transform asset-related data from various sources for both engineering and analytical purposes.
• Ensure data integrity, quality, and accessibility by implementing best practices in data engineering and management.
• Collaborate with stakeholders to understand their data requirements and translate them into technical specifications for both data engineering and analytics projects.
• Conduct data analysis to identify trends, patterns, and insights that inform asset management practices and decision-making.
• Develop and implement data models and analytics frameworks that support business objectives and enhance asset performance.
• Create and maintain dashboards and visualizations that effectively communicate asset performance metrics and analytics findings to stakeholders.
• Implement and manage data within the organisation's storage solutions (e.g., databases, data lakes) to facilitate efficient data retrieval, access and analysis.
• Work with cross-functional teams to prioritize and implement analytics-related user stories, ensuring timely delivery of data-driven insights.
• Document data engineering processes, data flows, and analytics workflows to support knowledge sharing and onboarding.
• Stay current with industry trends, tools, and best practices in data engineering and analytics to continuously improve processes and solutions.

What we are looking for

• Knowledge in Data Science, Computer Science, Engineering, or a related field.
• Relevant experience in both data engineering and data analytics, railway engineering or a similar role will be an advantage.
• Proficiency in data engineering tools, programming languages and data modelling techniques (e.g., Python, SQL, ETL tools) as well as analytics tools (e.g. Tableau, Power BI, LLM, ML models).
• Strong analytical and problem-solving skills, with a focus on data quality and performance optimization.
• Excellent written and verbal communication skills to effectively convey technical concepts to non-technical stakeholders.
• Ability to work independently and collaboratively in a team environment.
• A proactive mindset with a passion for leveraging data to drive improvements in asset management processes and outcomes.