
Data Product Services Engineer
- Kuala Lumpur
- Permanent
- Full-time
- Support the configuration, integration, and maintenance of data platforms used across the enterprise.
- Assist with CI/CD pipeline implementation and Infrastructure-as-Code (IaC) to increase automation and consistency.
- Help monitor and improve the performance, availability, and reliability of cloud-based data services.
- Collaborate on core security operations, including identity access management, system monitoring, and incident remediation.
- Participate in the design and deployment of data pipelines and platform features in cloud environments.
- Contribute to technical documentation, platform testing, and continuous improvement of engineering processes.
- Help ensure data systems meet internal compliance, governance, and security standards.
- Bachelor’s degree in technology, engineering, or a related field—or equivalent hands-on experience.
- 2–4 years of experience in IT, platform engineering, or data engineering roles.
- Familiarity with CI/CD tools and Infrastructure-as-Code frameworks such as Terraform, Azure Bicep, or AWS CDK.
- Scripting experience in Python, Java, or Scala for automation and integration tasks.
- Exposure to data pipeline technologies like Apache Airflow, Spark, and Kafka.
- Knowledge of cloud environments (AWS, Azure, GCP) and cloud-native data platforms.
- Understanding of data modeling concepts, data lakes, and SQL/NoSQL databases.
- Strong collaboration skills and comfort working within structured engineering workflows.
- Practical experience with Azure, AWS, Databricks, and Palantir platforms.
- Knowledge of data ingestion, transformation workflows, and pipeline architecture.
- Awareness of security best practices and enterprise data governance.
- Familiarity with data visualization tools (e.g., Power BI, Tableau).
- Exposure to distributed systems and batch/real-time data processing.
- Eagerness to learn, grow, and adapt in a dynamic data engineering environment.
- Experience working in globally regulated, compliance-focused environments.
- Familiarity with AI/ML-driven data engineering approaches to enhance workflow automation and efficiency.