Senior Engineer (Data Analytics & Applications)

Careers@Gov; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A governmental agency in Singapore is seeking a Data Scientist/Data Analytics Engineer to enhance asset management through data engineering and analytics. You will design data pipelines, collaborate with various teams, and create effective visualizations while ensuring data quality. The ideal candidate has a strong background in data science, relevant experience in data engineering, and proficiency in tools like Python and SQL. This role offers an opportunity to leverage data to improve asset management processes.

Qualifications

• Knowledge in Data Science, Computer Science, Engineering, or a related field.
• Relevant experience in data engineering and data analytics.
• Proficiency in data engineering tools and programming languages.

Responsibilities

• Design, develop, and maintain data pipelines for asset-related data.
• Ensure data integrity and quality by implementing best practices.
• Collaborate with stakeholders to translate data requirements.

Skills

Data Science

Data Engineering

Analytical skills

Problem-solving

Communication

Education

Degree in Data Science, Computer Science, or Engineering

Tools

Python

SQL

ETL tools

Tableau

Power BI

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.

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 prioritise 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 optimisation.
• 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.

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