Snapshot of the Role

In this role as the Senior Data Engineer, you will design, build and operate QL Group's enterprise data platform on Microsoft Fabric, delivering reliable, high-quality data that powers analytics, AI, and self-service BI across the organisation. You will work on Lakehouse architecture, data ingestion, ETL/ELT pipelines, data quality, performance optimisation and reusable analytics-ready data assets.

What You'll Be Driven To Do

Build and enhance QL Group's enterprise Lakehouse platform using Medallion Architecture principles.
Develop and optimise data ingestion from ERP, manufacturing, supply chain, finance and other enterprise systems.
Design, schedule and monitor ETL/ELT pipelines to ensure timely, accurate and reliable data delivery.
Apply data governance, access control and data quality standards to keep enterprise data secure and trusted.
Partner with business and IT stakeholders to translate requirements into effective analytics solutions, improving data accessibility, self-service adoption, and overall user satisfaction.
Deliver high-quality technical work on assigned projects, share expertise, and mentor junior team members to help raise data literacy across teams.
Support performance, cost optimisation and continuous improvement across the data platform

What You'll Need to Succeed

Bachelor's degree in Computer Science, IT, Data Science, Data Engineering or a related field. A Master's degree or relevant professional certification (e.g. Microsoft Fabric, Azure Data Engineer, Power BI Data Analyst, Databricks, or AWS/GCP data certifications) is an added advantage.
Minimum 4–6 years of hands-on experience in data engineering, BI, data warehousing or analytics.
Proven track record in delivering enterprise data pipelines, ingestion and integration frameworks, and analytics platforms within a complex, multi-system environment (ERP, financial, manufacturing, supply chain, and commercial systems).
Strong experience with Microsoft Fabric, OneLake, Azure Synapse, Azure Data Factory, SQL, Python and PySpark. Knowledge of Lakehouse design, Medallion Architecture, Parquet/Delta formats and dimensional data modelling.
Experience with data ingestion from enterprise systems, APIs, flat files and databases using CDC or incremental loading.
Strong communication, problem-solving and stakeholder management skills, with a practical, service-oriented mindset.
Willing to be based at Shah Alam, Selangor.

At QL, sustainability and innovation go hand in hand. Join us in building data-driven solutions that support a sustainable agrofood ecosystem and accelerate our digital transformation journey.