Powering the Future with AIDA

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To lead the next phase of our AI evolution, we’ve launched a new business unit AIDA – Artificial Intelligence & Data Analytics – a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.

At Singtel, this is more than a technology upgrade. It’s a strategic transformation that redefines how value is created across the enterprise core— augmenting human capabilities and unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processes under one cohesive strategy. Our mission is to build AI literacy, and foster a culture where intelligence empowers people.

We welcome you to join us on a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core. Grow with us in a workplace that champions innovation, embraces agility, and puts human potential at the heart of everything we do.

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Be a Part of Something BIG!  

• Responsible for building and supporting data ingestion and transformation pipelines in a modern hybrid cloud platform
• Develop basic batch and streaming pipelines, working with cloud tools such as Databricks and Kafka under the guidance of senior engineers
• Contribute to the delivery of reliable, secure, and high-quality data for analytics, reporting, and machine learning use cases
• Responsible for implementing knowledge base and retrieval-augmented generation (RAG) solution stack to support GenAI agentic use cases

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Make An Impact By

• Build and maintain data ingestion pipelines for batch and streaming data sources using tools like Databricks and Kafka
• Perform data transformation and cleansing using PySpark or SQL based on business and technical requirements
• Monitor and troubleshoot data workflows to ensure data quality and pipeline reliability
• Work closely with senior data engineers to understand platform architecture and apply best practices in pipeline design
• Assist in integrating data from diverse source systems (files, APIs, databases, streaming)
• Help maintain metadata and pipeline documentation for transparency and traceability
• Participate in integrating pipelines with tools such as Microsoft Fabric, Databricks, Delta Lake, and other platform components
• Implement and operate data virtualization layer to centralize visibility and control of data across diverse sources
• Contribute to automation efforts using version control and CI/CD workflows
• Apply basic data governance and access control policies during implementation

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Skills to Succeed

• Bachelor’s degree in Computer Science, Engineering, or a related field
• 1–3 years of experience in data engineering or data platform development
• Proven ability to independently build basic batch or streaming data pipelines
• Hands-on experience with Python and SQL for data transformation and validation
• Familiarity with Apache Spark (especially PySpark) and large-scale data processing concepts
• Self-starter with strong problem-solving skills and a keen attention to detail
• Able to work independently while collaborating effectively with senior engineers and other stakeholders
• Strong documentation and communication skills