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Company Overview
A leading Singapore-based financial institution, established in 1932, is committed to helping individuals and businesses achieve their aspirations. The organization combines deep customer understanding with technology and creativity to deliver innovative financial solutions, modernize operations, and drive a sustainable future. The company fosters a collaborative, supportive, and future-ready work environment where employees can grow their careers while contributing meaningful value to the community.
Summary
The Data Engineer will design, build, and operate scalable, cloud-native data platforms that enable analytics, reporting, and informed decision-making across the organization. This role emphasizes modern data engineering practices, including Lakehouse architectures, real-time streaming, automation, and data governance, while supporting regional initiatives via a Centre of Excellence model.
Responsibilities
Deliver robust, scalable, and secure data pipelines aligned with group architecture standards
Modernize legacy data workloads to cloud-native or hybrid platforms
Collaborate with Business Units, Analytics, and regional teams to provide analytics-ready datasets and support dashboards and reporting
Contribute to regional data initiatives and capability uplift through build-and-transfer models
Design, build, and maintain scalable data pipelines across hybrid environments (on-prem and cloud), preferably with AWS
Develop and support batch and real-time data processing using streaming technologies
Implement and operate Lakehouse architectures and open metadata/catalog frameworks
Build automated ETL/ELT workflows, data quality checks, monitoring, and scheduling frameworks
Ensure operational stability, performance optimization, and continuous improvement of data platforms
Qualifications
Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or related discipline
3–7 years of relevant experience in data engineering, data platforms, or analytics engineering
Strong proficiency in SQL, dbt, Airflow/Dagster, Git, and CI/CD practices
Proven experience with Apache Iceberg and Lakehouse architectures; proficiency in Spark and PySpark
Experience with at least one major cloud platform (preferably AWS), including storage, compute, data processing, streaming, and orchestration services
Strong Python programming skills for data engineering and automation
Experience with Data Virtualization tools and supporting dashboards or data visualizations (e.g., Power BI)
Familiarity with Hadoop ecosystem, relational databases, data lakes, and data warehouses
Strong analytical and problem-solving skills
Excellent communication and collaboration skills with diverse stakeholders
Ability to work independently, manage priorities in a fast-paced environment, and adopt new technology
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.
1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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