Senior Data Engineer

About the role

Great Eastern, a well-established insurance group founded in 1908 and part of OCBC, is looking for a Senior Data Engineer to design, develop and maintain robust data pipelines and ETL solutions. The role works closely with cross-functional teams to ensure data quality, scalability and alignment with business and technical requirements.

Key responsibilities

• Design, develop, test and maintain scalable ETL pipelines, collect and integrate new datasets, and maintain documentation and data mappings across systems.
• Create optimized, scalable data models aligned with data architecture standards and best practices.
• Conduct code reviews, rigorous testing and solution design reviews to ensure high-quality deliverables.
• Implement monitoring, logging and alerting systems, and build reliable data marts in the Hadoop ecosystem for planning, reporting and analytics.
• Manage code in a centralized repository with clear branching strategies and documented commits, and coordinate stakeholder testing and deployment.
• Act as business process owner for onboarding users and data products onto the data platform, and architect end-to-end analytics solutions such as dashboards and statistical models.
• Proactively improve data engineering processes and workflows, and monitor pipelines continuously to troubleshoot and optimize performance.

Required profile

• Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Software Engineering or an equivalent field, or proven data engineering experience.
• At least 5 years of experience in Business Intelligence / Data Analytics, with a track record of delivering data-driven business solutions.
• Stakeholder management: able to explain data analytics issues to business users and other stakeholders.
• Strong communication, problem-solving and teamwork skills, with the ability to work under pressure and during peak periods.
• Understanding of banking, insurance and financial services is preferred.

Required skills

• Proficiency in Hadoop, Spark, Hive and cloud data services such as AWS, Azure or GCP.
• Hands-on experience with large volumes of data using SQL, Spark, Hadoop or other big data ecosystems is preferred.
• Proven experience in data engineering, ETL development and big data technologies.