Data Engineer Intern (Pipeline Development & Enhancement)

Design & Planning Lab (DPLab) is a group within URA driving URA’s Urban Planning & Design Technology Centre of Excellence (URBEX) efforts. Our teams with capabilities in software development, geospatial analytics, urban design modelling & simulation, data science, AI / ML, data engineering, data governance and management, work closely with planners, architects, policy makers across various agencies, as well as external partners, to generate insights and develop tools and solutions to tackle Singapore's urban planning challenges. The Data Engineering (DE) Team in the Urban Redevelopment Authority (URA) is responsible for applying advanced methods in data engineering to enhance various aspects of urban planning and development. The team comprises data engineers, analysts, cloud engineer, and planners who work together to provide innovative solutions to complex urban challenges. This role will be an internship under DPL DE team.

Data Pipeline Development and Enhancements for PSDH • Build and improve data pipelines that power the flow of data into the PSDH Data Lakehouse using SQL, Python, Azure Data Factory, and Databricks. • Transform raw data into reliable, usable datasets while ensuring data quality, consistency, and performance. • Explore ways to make workflows faster, more stable, and easier to maintain through optimization and automation. • Investigate data or system issues and contribute to practical solutions that improve platform reliability and user experience. • Collaborate with users to understand data needs, onboard new data sources, and support adoption of the platform. • Identify opportunities to enhance how the platform works, feels, and is used - and help turn ideas into tangible improvements. • Contribute to initiatives that improve monitoring, reporting, governance, and overall accessibility of insights. • Capture and share knowledge through documentation, resources, or other materials that make the platform easier to understand and use. Learning Outcomes • Gain exposure to how large-scale data platforms are designed and operated to support critical, real-world use cases. • Build strong foundations in data engineering with SQL, Python, and cloud-native tools (Azure, Databricks) through hands-on work. • Learn to design and optimize scalable data pipelines in development environments, with insight into how they support production systems. • Understand how data governance, security, and reliability are implemented in high-trust environments handling sensitive data. • Develop an engineering mindset: break down problems, troubleshoot issues, and contribute to improvements that enhance platform performance and usability. • Collaborate with stakeholders to translate data needs into practical, well-structured solutions that support decision-making. • Deliver meaningful, portfolio-ready work while contributing to systems that enable better data use at scale. #LI-URAINTERNSHIP

• Internship Period: May - Aug 2026. Full-time internship preferred. Note: To facilitate the hiring process, please state your availability, including specific start and end date in your resume or application form. • Undergraduate students pursuing Computer Science / Information Technology, or relevant studies. • Familiarity with SQL, Python, Jenkins, Git. • Knowledge in Azure Cloud (e.g. Azure Data Factory, Azure Databricks) is an added advantage.