Intern, Data Engineer
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Summary
Internship on PhillipCapital's IT team in Singapore: the intern helps build, test, and maintain data pipelines, integrations, and warehouse tables powering reporting, analytics, and AI initiatives, working with SQL and at least one language (e.g. Python or Java) while learning ETL, data quality, and automation practices.
We're looking for a Data Engineer Intern to join our IT team in Singapore, where you'll gain hands-on experience building and supporting reliable data pipelines, data integrations, and data platforms that enable trusted reporting, automation, analytics, and AI initiatives across the organization.
What You'll Do
Assist in building, testing, and maintaining data pipelines for extracting and transforming data from multiple source systems.
Support data ingestion, validation, and quality checks to ensure data is accurate and reliable.
Help maintain data warehouse tables, data models, and curated datasets used for reporting and analytics.
Work with data analysts, data scientists, and IT teams to understand technical data requirements.
Assist in automating data workflows, scheduled jobs, and recurring data processing tasks.
Support troubleshooting of pipeline failures, data load errors, and data quality issues.
Gain exposure to database management, data integration, data quality monitoring, query optimization, and performance tuning practices.
Document data flows, source-to-target mappings, and pipeline logic for knowledge sharing and maintainability.
Explore new tools and technologies that can improve data engineering, data automation, platform reliability, and analytics readiness.
What We're Looking For Currently pursuing a Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related technical field. Basic experience with SQL and at least one programming language, such as Python, Java, Scala, C#, or C++. Interest in databases, data warehousing, ETL/ELT processes, data pipelines, batch processing, and enterprise data platforms. Basic understanding of data modelling, data integration, data quality checks, and source-to-target data mapping concepts. Good analytical and technical problem-solving skills, with strong attention to data accuracy and reliability. Willingness to learn data engineering tools, automation practices, database optimization, and platform reliability best practices. A proactive team player who can communicate technical concepts clearly and work collaboratively with data analysts, data scientists, and IT teams.
Why This Role Gain practical experience building and supporting the data pipelines, integrations, and warehouse structures that form the foundation of enterprise analytics and AI initiatives. Work with a dynamic, innovative team on real-world data engineering, automation, and platform reliability improvement initiatives. Be part of a forward-thinking environment that values technical learning, reliable data foundations, and continuous improvement.
What We're Looking For Currently pursuing a Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related technical field. Basic experience with SQL and at least one programming language, such as Python, Java, Scala, C#, or C++. Interest in databases, data warehousing, ETL/ELT processes, data pipelines, batch processing, and enterprise data platforms. Basic understanding of data modelling, data integration, data quality checks, and source-to-target data mapping concepts. Good analytical and technical problem-solving skills, with strong attention to data accuracy and reliability. Willingness to learn data engineering tools, automation practices, database optimization, and platform reliability best practices. A proactive team player who can communicate technical concepts clearly and work collaboratively with data analysts, data scientists, and IT teams.
Why This Role Gain practical experience building and supporting the data pipelines, integrations, and warehouse structures that form the foundation of enterprise analytics and AI initiatives. Work with a dynamic, innovative team on real-world data engineering, automation, and platform reliability improvement initiatives. Be part of a forward-thinking environment that values technical learning, reliable data foundations, and continuous improvement.