Intern, DAT

Singapore Land Authority; Singapore; On-site; SGD 13,000 - 20,000; Full time

Job summary

Singapore Land Authority is seeking an intern to support the Enterprise Data Platform team in delivering core data engineering and data management functions. You will assist with data ingestion, profiling, and preparation to ensure high-quality data for analytics and operations.

You will gain hands-on experience with data platforms, pipelines, and data quality practices while collaborating with data engineers and business stakeholders on ongoing initiatives.

Qualifications

• Pursuing tertiary qualifications in Data Science, Computer Science, or a related technical field.
• Strong analytical skills with demonstrable experience in data analysis tools, preferably Python and SQL.
• Ability to write efficient, well‑documented code and think critically about edge cases and error handling.
• Familiarity with data management concepts, data engineering techniques, and ETL processes.

Responsibilities

• Assist in the development of data models for various business domains.
• Work with stakeholders to understand data requirements and translate them into conceptual, logical, and physical data models.
• Develop and maintain data transformation processes, including data cleansing, enrichment, normalization, and aggregation, to ensure the integrity and performance of data models.
• Analyse data from diverse sources and map it to existing data models and schemas.
• Participate in data validation and testing to ensure the accuracy and completeness of mapped data.
• Contribute to the documentation of data modelling standards and best practices.

Skills

Data modelling

Python

SQL

ETL

Data analysis

Education

Bachelors in Data Science/Computer Science

Job description

What the role is:

The intern will support the SLA Enterprise Data Platform (EDP) team in delivering core data engineering and data management functions. The role involves assisting with data ingestion, data profiling, and data preparation to ensure high-quality, reliable data is available for analytics and business operations. The intern will gain hands‑on experience with enterprise data platforms, data pipelines, and data quality practices while working closely with data engineers and business stakeholders to support ongoing data initiatives.

What you will be working on:

• Assist in the development of data models for various business domains.
• Work with stakeholders to understand data requirements and translate them into conceptual, logical, and physical data models.
• Develop and maintain data transformation processes, including data cleansing, enrichment, normalization, and aggregation, to ensure the integrity and performance of data models.
• Analyse data from diverse sources and map it to existing data models and schemas.
• Participate in data validation and testing to ensure the accuracy and completeness of mapped data.
• Contribute to the documentation of data modelling standards and best practices.

What we are looking for:

• Pursuing tertiary qualifications in Data Science, Computer Science, or a related technical field
• Strong analytical skills with demonstrable experience in data analysis tools, preferably Python and SQL
• Ability to write efficient, well‑documented code and think critically about edge cases and error handling
• Familiarity with data management concepts, data engineering techniques, and ETL processes
• Strong communication skills and ability to work effectively in a team environment
• Adaptability and willingness to learn
• Responsible and proactive
• Able to commit full time from August 2026 to December 2026 / September 2026 to March 2027 for at least 4 to 6 months.
• Please include your availability in your CV.

About Singapore Land Authority

The mission of the Singapore Land Authority is to optimise land resources for the economic and social development of Singapore. It ensures the best use of State land and buildings, provides an effective and reliable land management system and enables the full use of land information for better land management.