Data & AI Operations Engineer

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

Job summary

A leading telecommunications company in Singapore is seeking a Data & AI Platform Engineer to build and maintain data ingestion and transformation pipelines. The ideal candidate will have a Bachelor's degree in Computer Science or a related field, along with experience in data engineering. This is a full-time, entry-level role offering opportunities to work with cloud tools like Databricks and Kafka.

Qualifications

• 1–3 years of experience in data engineering or data platform development.
• Proven ability to independently build basic batch or streaming data pipelines.
• Self-starter with strong problem-solving skills and keen attention to detail.

Responsibilities

• Build and support data ingestion and transformation pipelines.
• Develop batch and streaming pipelines using cloud tools.
• Monitor and troubleshoot data workflows for quality.

Skills

Python

SQL

Apache Spark (PySpark)

Data Transformation

Data Governance

Education

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

Tools

Databricks

Kafka

Job description

Data & AI Platform Engineer- #AIDA – Singtel

Powering the Future with AIDA. To lead the next phase of our AI evolution, we’ve launched the AIDA business unit – Artificial Intelligence & Data Analytics – a strategic engine driving our transformation. Our mission is to build AI literacy and foster a culture where intelligence empowers people.

Responsibilities

• Build and support 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.
• Implement knowledge base and retrieval‑augmented generation (RAG) solution stack to support GenAI agentic use cases.
• 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.

Qualifications

• 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.

Seniority level

Entry level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Telecommunications