Intern, Data Engineer

AIA Digital+ is a Technology, Digital and Analytics innovation hub dedicated to powering AIA to be more efficient, connected and innovative as it fulfils its Purpose to help millions of people across Asia-Pacific live Healthier, Longer, Better Lives.

As an Intern, Data Engineer, you will support the design, development, and optimization of modern data pipelines and analytics solutions using Databricks, Python, SQL, and GitHub Copilot. You will collaborate with data engineers and solution architects to build scalable data workflows, improve data quality and accessibility, and leverage AI tools to accelerate development productivity.

Responsibilities:

• Assist in designing, developing, and maintaining data pipelines using Databricks.
• Build and optimize ETL/ELT processes to ingest, transform, and load data from multiple sources.
• Support the development of scalable data models and data products.
• Perform data quality validation, monitoring, and troubleshooting activities.
• Document data pipelines, workflows, and technical solutions.
• Work with cloud-based data platforms and modern data architectures.
• Assist in integrating data from databases, APIs, files, and enterprise applications.
• Support implementation of best practices for data governance, security, and performance optimization.
• Participate in testing and deployment activities.
• Leverage GitHub Copilot to accelerate code development and improve productivity.
• Explore the use of AI-powered development tools for coding, documentation, testing, and troubleshooting.
• Contribute to proof-of-concepts involving Generative AI for data engineering use cases.
• Learn and apply prompt engineering techniques to improve development outcomes.
• Participate in Agile ceremonies, team meetings, and technical discussions.
• Collaborate with data engineers, architects, analysts, and product stakeholders.
• Research emerging technologies and recommend innovative approaches to improve development efficiency.
• Present internship project outcomes and lessons learned to the team.

Requirements:

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Information Technology, Artificial Intelligence, or a related field.
• Basic knowledge of Python, SQL, and software development concepts.
• Understanding of data engineering fundamentals, including databases, ETL/ELT processes, and data pipelines.
• Familiarity with Git/GitHub and an interest in AI-assisted development tools such as GitHub Copilot.
• Exposure to Databricks, Apache Spark, cloud platforms, or analytics technologies is an advantage.
• Strong analytical thinking, problem-solving abilities, and eagerness to learn new technologies