全职 Data Engineer 工作, 薪水, MR DIY International Selangor 公司招聘中 - Ricebowl

At MR DIY International, we're more than a global home improvement brand, we're a catalyst for ambitious talent ready to grow beyond borders.

With over 5,000+ stores across 14 countries globally, we offer unmatched international exposure to those looking to build a meaningful, global career. From retail operations and merchandising to strategy, tech, and supply chain. Your work here shapes how millions of customers shop every day.

Job Summary

The Data Engineer is a key technical contributor to the organisation's data infrastructure, reporting directly to the Head of Data. This role focuses on the hands-on execution of modernising our company’s data ecosystem and upholding engineering excellence. You will ensure the reliability of our data infrastructure and foster a high-performing culture.

Key Responsibilities

• Support the Head of Data and Principal Data Engineers in executing the long-term data strategy, contributing to the development of architecture, tooling, and engineering best practices.
• Design and implement highly scalable, secure, and reliable data pipelines, with end-to-end observability (monitoring, logging, alerting, data quality checks, and automated error handling).
• Build and maintain a modern data architecture, including orchestration frameworks, transformation layers with dbt, and a medallion data model that supports analytics and operational use cases.
• Uphold engineering excellence by adhering to strict standards in version control, CI/CD pipelines, branching strategies, Infrastructure-as-Code, documentation, and code review practices.
• Implement strong data governance and security practices within the codebase, including access controls, encryption, privacy compliance, metadata management, naming conventions, and lifecycle management.
• Optimise data platform performance and cost by monitoring usage, improving query efficiency, and managing resources across storage and compute workloads.
• Partner with analytics engineers to ensure the delivery of trusted, reliable insights to business stakeholders via governed self-service.

Job Requirements

• 2 to 4 years of experience in data engineering or similar roles.
• Exposure to the modern data stack (Google Cloud, BigQuery, dbt, Airflow, Looker or similar).
• Experience building pipelines for heterogeneous data sources (ERP, SaaS, APIs, spreadsheets, etc.).
• Experience in troubleshooting and resolving performance bottlenecks across the entire data stack, e.g. query optimization, resource allocation, storage management, etc.
• Understanding of dimensional modelling (Kimball) and data warehouse best practices.
• Familiarity with DevOps for data: version control, CI/CD, infrastructure as code, monitoring, and observability.
• Knowledge of data governance, compliance, and security frameworks.
• Good communication skills, able to bridge technical and business perspectives.