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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-learn (nice to have).
  • Cloud data tools: Redshift, S3, EMR, SageMaker.
  • Dashboarding: QuickSight, Tableau, or Power BI.
  • Bonus: AWS certifications (Data Analytics, Machine Learning Specialty) and Generative AI experience such as prompt engineering or LLM fine-tuning.

Key attributes for success

  • Problem-solver: you debug data chaos and optimise pipelines.
  • AI explorer: you are curious about GenAI's role in data engineering, such as synthetic data generation.
  • Visual storyteller: you turn complex data into clear, impactful visualisations.
  • Team player: you thrive in cross-functional teams with data scientists, business analysts and engineers.

Qualifications

  • Bachelor's degree in Computer Science, Data Science, or related fields, or equivalent experience.
  • Experienced candidates: 3+ years building and fine-tuning data pipelines.
  • Fresh graduates with prior hands-on data or AI projects, academic or personal, are welcome to apply.

Ready to apply?

Submit your application and tell us why this role fits you. Attach whatever shows your work best: resume, GitHub profile, code samples, links to personal projects.

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