Back to SearchSenior Data Engineer (Cloud)
Hybrid in Malaysia: Kuala Lumpur
Data Software Engineering& 4 others
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We are seeking a Senior Data Engineer to design, build and run reliable ETL and ELT pipelines for enterprise data platforms. You will use Python, SQL and Apache Airflow with cloud services across Microsoft Azure, Google Cloud Platform (GCP) or Amazon Web Services (AWS). You will troubleshoot issues, improve delivery automation and partner with clients on requirements and trade-offs.
Responsibilities
- Design and build scalable ETL and ELT pipelines using Python, SQL and cloud-native services
- Write, optimize and troubleshoot complex SQL for transformations, validation and performance
- Create and maintain data models and warehouse structures that support quality, availability and scale
- Orchestrate workflows in Apache Airflow including scheduling, monitoring and incident resolution
- Support pipeline delivery and platform operations across Azure, Google Cloud Platform (GCP) or Amazon Web Services (AWS)
- Improve continuous integration and continuous delivery (CI/CD), source control and automated deployment for data solutions
- Investigate data, integration and infrastructure issues, drive root-cause analysis and implement fixes
- Collaborate with clients and cross-functional teams to align on requirements, risks, dependencies and delivery plans
Requirements
- Hands-on experience building ETL and ELT pipelines and supporting data warehousing
- Advanced SQL skill sets including optimization, data validation and complex transformations
- Python proficiency for pipeline development and software engineering practices
- Experience with distributed processing using PySpark or Apache Beam
- Practical cloud experience with Microsoft Azure, Google Cloud Platform (GCP) or Amazon Web Services (AWS) for data workload
- Workflow orchestration background with Apache Airflow or Google Cloud Composer
- Knowledge of data modeling, data lifecycle management and data quality control
- Clear communication with the ability to explain trade-offs, risks and solution options to stakeholders
Nice to have
- Infrastructure as code exposure using Terraform or Kubernetes
- Streaming familiarity with Kafka and event-driven patterns
- Data integration tooling experience with Fivetran