AI Data Engineer

Michael Page; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive package with strong career

Opportunity to work on cutting-edge AI

Exposure to enterprise-scale platforms

Job summary

Michael Page Singapore is seeking a seasoned Data Engineer to design, build and support large-scale batch and real-time data pipelines on modern cloud platforms. You will craft robust data integration across APIs, databases, files, and event-driven systems, while contributing to GenAI use cases.

The role requires 5+ years in data engineering, hands-on with Databricks, Spark, SQL, Python, Kafka, and Delta Lake, plus knowledge of CI/CD, data governance and platform operations.

Qualifications

• Five+ years of data engineering or cloud data platform delivery experience.
• Strong hands-on experience with Databricks, Spark (PySpark) and SQL.
• Exposure to Python, Kafka, Delta Lake, and Microsoft Fabric is advantageous.
• Proven ability to design and support production-grade batch and streaming pipelines.
• Knowledge base and Retrieval-Augmented Generation (RAG) solutions, embeddings, and GenAI apps.

Responsibilities

• Design, develop, and support large-scale batch and real-time data pipelines on cloud platforms.
• Build robust data integration across APIs, databases, files, and event-driven systems.
• Develop and maintain knowledge repositories and retrieval-based AI solutions for GenAI use cases.
• Provide technical leadership on platform architecture, code quality, deployment standards.
• Drive platform reliability via monitoring, troubleshooting, release management, and continuous improvement.

Skills

Data engineering

Cloud data platform delivery

CI/CD

Stakeholder communication

GenAI

Education

Degree in Computer Science, Engineering, Information Systems

Tools

Databricks

Apache Spark (PySpark)

SQL

Python

Kafka

Delta Lake

Microsoft Fabric

Job description

• Competitive package with strong career growth potential
• Permanent position with stable work environment

• Competitive package with strong career growth potential
• Permanent position with stable work environment

About Our Client

Our client is a well-established organisation investing heavily in modern cloud, data, and AI capabilities to enable digital transformation and innovation across multiple business functions.

Job Description

• Design, develop, and support large-scale batch and real-time data pipelines on modern cloud platforms.
• Build robust data integration solutions across APIs, databases, files, and event-driven systems.
• Develop and maintain knowledge repositories and retrieval-based AI solutions to support emerging GenAI use cases.
• Provide technical leadership on platform architecture, code quality, deployment standards, and operational excellence.
• Drive platform reliability through monitoring, troubleshooting, release management, and continuous improvement initiatives.

The Successful Applicant

• Degree in Computer Science, Engineering, Information Systems, or a related discipline
• At least 5 years of experience in data engineering or cloud data platform delivery.
• Strong hands-on experience with Databricks, Apache Spark (PySpark), and SQL, with exposure to technologies such as Python, Kafka, Delta Lake, and Microsoft Fabric considered advantageous.
• Proven track record designing and supporting production-grade batch and streaming pipelines, including orchestration, monitoring, troubleshooting, and performance optimisation.
• Experience implementing Knowledge Base and RAG solutions, including embeddings, vectorisation, retrieval mechanisms, and GenAI applications.
• Good understanding of CI/CD, data governance, cloud security, access management, and platform operations, with strong stakeholder communication skills.

What's on Offer

• Competitive package with strong career growth potential
• Opportunity to work on cutting-edge cloud, data, and AI transformation programmes.
• Exposure to enterprise-scale platforms, stakeholders, and high-impact business initiatives.