Senior Data Engineer

Quess Singapore; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Quess Singapore is seeking an experienced Data Engineer to design, build and optimise scalable data pipelines and platforms that support analytics, reporting and decision-making.

You will work with business and technology teams, lead data engineering initiatives across Hadoop/Spark/Hive environments, and help ensure data quality and performance in a Life Insurance context. This role requires strong problem-solving and independent work in a fast-paced environment.

Qualifications

• 5+ years of experience in Data Engineering / ETL.
• Experience with Hadoop, Spark, Hive or similar big data technologies.
• Experience with AWS, Azure or GCP.
• Strong understanding of data modelling, data pipelines and data architecture.
• Life Insurance experience is highly preferred.

Responsibilities

• Design, build and maintain scalable ETL/data pipelines.
• Develop data models and data marts for analytics and reporting.
• Collaborate with business and technical stakeholders on data requirements.
• Lead code reviews, testing and production deployments.
• Troubleshoot and optimise pipeline performance.

Skills

Data Engineering

ETL

Big Data

Cloud Platforms

Stakeholder Management

Tools

Hadoop

Spark

Hive

AWS

Azure

GCP

Job description

We’re looking for an experienced Data Engineer to build and optimise scalable data pipelines and data platforms. You’ll work closely with business and technology teams to deliver reliable, high-quality data solutions that support analytics, reporting and business decision-making.

What you’ll do

• Design, build and maintain scalable ETL/data pipelines
• Develop data models and data marts for analytics and reporting
• Work with large datasets and improve data quality, reliability and performance
• Build monitoring, logging and alerting for data pipelines
• Collaborate with business and technical stakeholders on data requirements
• Lead code reviews, testing and production deployments
• Troubleshoot and optimise pipeline performance
• Drive improvements across data engineering processes and architecture
• Support data solutions within a Life Insurance environment

What we’re looking for

• 5+ years of experience in Data Engineering / ETL
• Strong experience with Hadoop, Spark, Hive or similar big data technologies
• Experience with AWS, Azure or GCP
• Strong understanding of data modelling, data pipelines and data architecture
• Life Insurance experience is highly preferred
• Strong problem-solving and stakeholder management skills
• Comfortable working independently in a fast-paced environment