Data Management & Engineering Intern (Technical)

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. Within DPLab, the Planning Sectoral Data Hub team is developing a strategy and system to drive the fusion and distribution of key datasets for planning work across multiple government agencies. The team’s challenge is multi-faceted - stretching from data governance, technical solutioning to data engineering – as it lays the foundation for better planning.

The intern shall assist Data Managers & Data Engineers in the following tasks: • Manage the dataset lifecycle by documenting the entire data management policy and process from data pre-acquisition to data archival or destruction. • Set up processes for future Data management. • Work with other agencies to align data attributes and schema based on planning use cases, understand the datasets fully, ensuring proper access and use of the datasets, and work with Data Engineers to collect and fuse data, maintain the datasets and storage, rectify any issues and errors faced with the datasets. • Work on dashboard prototypes & geospatial analytics using sample data to represent how dataset can be used to tackle policy & urban planning issues. • Assist in designing and building data pipelines to enable efficient data flow from the source system to the PSDH Data Lakehouse. Utilize SQL and Python for ETL processes, and leverage Azure cloud services such as Azure Data Factory for pipeline orchestration and Azure Databricks for data processing, ensuring efficiency, scalability, and data integrity throughout the process. The intern is expected to reap the following learning outcomes: • Develop a good understanding of the lifecycle of dataset management, including acquisition, cleaning, transformation, storage, and archival/destruction (if applicable), which is crucial for ensuring the quality and security of data in urban planning. • Develop competency in managing/driving collaboration with cross-functional teams and in implementing data governance policies which are essential for developing and maintaining data products and solutions that meet business requirements and support planning studies and processes. • Develop competency in data governance and management tools; and understanding of emerging trends and technologies which are critical in enhancing the effectiveness of data-driven planning and analytical insights in the Urban Planning & Design domain. • Data Pipeline Engineering: Gain hands-on experience in designing, building, and managing data pipelines, utilizing SQL and Python for data transformation and transport, and leveraging cloud technologies like Azure Data Factory for orchestration and Azure Databricks for ETL processes. • Develop an understanding of the PSDH Data Lakehouse framework, including key components and design principles. Learn how to implement data governance policies to ensure data quality and compliance.

Interns who are able to commit between Jan - Aug 2025 for 3-6 months. Full-time internship preferred. NOTE: To facilitate the hiring process, please state your availability (part-time or full-time), including specific start and end date in your resume or application form. • Students working toward a Degree or other related qualification in Computer Science, Information Technology, or an urban planning and design related field (e.g. Architecture). • Computer Science / IT; Business Analytics; Architecture; Smart Cities; Data Science, Engineering; • Foundational knowledge in data governance and management, business analysis and data analytics • Resourceful in problem solving, with attention to detail. • Strong communication and collaboration skills • Familiarity with SQL, Python, Git • Familiarity with handling data and running data analytics projects Good to Have: • Knowledge in Azure Cloud (e.g. Azure Data Factory, Azure Databricks) and Jenkins will be an added advantage. • Relevant experience working with data managers or data engineers in data-related projects. We regret to inform that only shortlisted candidates will be notified.