Data Engineer
We are looking for a Data Engineer who takes pride in building data infrastructure that actually works — reliably, at scale, and in production. This is a hands-on engineering role where you will design and deliver the pipelines, data models, and workflows that power analytics, AI, and business decision-making across the organisation.
If you care about data quality, clean architecture, and engineering that stands up under pressure, this role is for you.
What You'll Be Doing
- Design, build, and maintain scalable data pipelines and data stores supporting analytics, reporting, and operational use cases
- Develop and optimise ingestion, transformation, and orchestration workflows across structured and unstructured data sources
- Embed data quality, lineage, reliability, and security controls throughout the engineering lifecycle
- Collaborate with analysts, data scientists, and business stakeholders to translate requirements into robust data models and reusable datasets
- Monitor and troubleshoot data jobs, improve pipeline performance, and support production operations and incident resolution
- Contribute to technical documentation, coding standards, and deployment and testing automation
What We're Looking For:
- Strong proficiency in SQL and data modelling — you can design and optimize schemas for performance and scalability
- Hands-on experience building ETL/ELT pipelines — from ingestion through transformation to delivery
- Solid Python skills and practical experience with cloud data platforms (AWS, Azure, or GCP)
- Minimum 2 years of experience in a data engineering or closely related role
- Bachelor's Degree in Computer Science, Information Systems, Data Science, or a relevant field
Good to have:
- Experience with Spark or distributed data processing frameworks
- Familiarity with data warehousing and data lake concepts and architectures
- Understanding of data governance, security practices, and CI/CD pipelines for data workflows
Singapore
雇用機会の均等化に関する声明
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