Data & AI Platform Engineer- #AIDA

Singtel Group; Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

A leading telecommunications company located in Singapore is seeking a Data Engineer to build and maintain data ingestion pipelines for batch and streaming sources. The candidate will work with tools like Databricks and Kafka, perform data transformation with SQL and Python, and ensure data quality in workflows. Ideal for those with a Bachelor's in Computer Science and 1-3 years of experience in data engineering. Join us to drive AI transformation and innovation in the telecom industry.

Qualifications

• 1–3 years of experience in data engineering or data platform development.
• Hands-on experience with Python and SQL for data transformation.
• Self-starter with strong problem-solving skills.

Responsibilities

• Build and maintain data ingestion pipelines for batch and streaming data sources.
• Monitor and troubleshoot data workflows to ensure data quality.
• Contribute to automation efforts using version control and CI/CD workflows.

Skills

Data ingestion

Data transformation

SQL

Python

Problem-solving

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Databricks

Kafka

PySpark

SQL

Job description

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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 capabilitiesand unlocking entirely new potential. It is a transformation journey by aligningpeople, platforms, and processesunder one cohesive strategy. Our mission is to buildAI literacy, and foster a culture whereintelligence empowers people.

We welcome you to join uson a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core.Grow with usin a workplace that championsinnovation, embracesagility, and putshuman potentialat the heart of everything we do.

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

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

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