Data Engineer

About the Role

We are seeking a Software Developer to join a high-performing enterprise data team responsible for delivering and supporting critical data ingestion capabilities across a large-scale data platform. This role is pivotal in re-architecting legacy data pipelines into modern, scalable systems and building robust backend services that support investment decision-making at scale.

This role is ideal for engineers who take pride in clean, well-tested code, and want to play a part in large-scale data transformation.

Responsibilities

• Design and develop scalable Python backend services for data systems.
• Build and maintain clean, modular, and test-driven code (unit and integration tests using TDD).
• Design, develop, maintain, and enhance data ingestion pipelines supporting ongoing operational requirements.
• Ingest and process data from external providers and internal sources into enterprise data platforms.
• Support BAU operations, including monitoring, troubleshooting, maintenance, and issue resolution for production workloads.
• Build enhancements to existing data engineering solutions and contribute to continuous platform improvements.
• Transform legacy data pipelines into modern, maintainable architectures.
• Collaborate closely with data engineers, backend engineers, and devops engineers for smooth deployments.
• Ensure high code quality, readability, and maintainability following best practices.
• Participate in code reviews, technical discussions, and agile ceremonies.

Must-Have Skills:

• 5+ years of experience in backend software engineering, primarily using Python.
• Strong Python backend development experience.
• Solid SQL skills and experience working with large-scale datasets.
• Proficiency in writing unit and integration tests using TDD principles.
• Experience with Python package management tools (Poetry, Conda, UV, Pip).
• Experience supporting production data platforms and troubleshooting operational issues.

Tech Stack & Tools

• Languages: Python (required), SQL (required)
• Database: Snowflake, Databricks
• DevOps: Kubernetes, Docker, CI/CD
• Testing: PyTest, TDD practices

Nice-to-Have Skills:

• Familiarity with Snowflake.
• Working knowledge of Databricks (basic to intermediate level).
• AWS cloud experience.
• Kubernetes, Docker, and CI/CD pipelines
• Financial services or regulated industry experience.
• Exposure to modern data architecture and cloud-based data platforms.

Why Join?

• Work on large-scale, business-critical data platforms used across the organisation.
• Gain exposure to modern technologies including Snowflake and Databricks.
• Participate in platform modernisation initiatives aligned to the organisation's future AI roadmap.
• Develop expertise in complex external data ingestion and enterprise-scale data operations.
• Opportunity to make an immediate impact within a high-visibility, production-critical environment.

We regret to inform that only shortlisted candidates will be notified

EA Registration No: R25158204, Wong Lin, Rachel

Allegis Group Singapore Pte Ltd, Company Reg No. 200909448N, EA Licence No. 10C4544