Data Engineer

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Data Engineer Build and optimise ETL pipelines for structured and unstructured data using PySpark, AWS Glue and Redshift, deploy serverless workflows on Lambda and Step Functions, and build dashboards in QuickSight or Tableau. Data & AI · Malaysia / Indonesia · Full-time About the role We are bridging data engineering with AI to solve real-world challenges, and we are looking for a Data Engineer who thrives on building scalable data pipelines. Whether you are a fresh graduate with a passion for data or an experienced engineer ready to build data pipelines, this role lets you work with PySpark in a hybrid environment. Data engineering Develop and optimise ETL pipelines for structured and unstructured data using PySpark, Glue, and Redshift. Ensure data integrity, security, and scalability across all pipelines. Dashboards and visualisation Develop interactive dashboards using QuickSight or Tableau to visualise complex datasets. Collaborate with stakeholders to translate data into business insights. Performance optimisation Fine-tune PySpark jobs and SQL queries for cost and performance efficiency. Proactively monitor and resolve data pipeline bottlenecks. AWS and cloud-native development Deploy and manage serverless data workflows with Lambda and Step Functions. Stay ahead of AWS's latest data and AI services, such as Amazon Q and new SageMaker features. Technical skills PySpark and AWS Glue for large-scale ETL and data processing. AI/ML frameworks: TensorFlow, PyTorch, Scikit-l

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