Data Engineer

2 weeks ago

Greater Kuala Lumpur, Malaysia Cradle Fund Full time 80,000 - 120,000 per year

The Data Engineer is responsible for assisting in the design and development of data pipelines that enable reliable, timely, and scalable data flow across the organization. This role ensures that business intelligence and analytics teams have access to clean, consistent, and well-structured data to support data-driven decision-making.

Key Responsibilities

  • Assist in designing, building, and maintaining ETL/ELT pipelines to move and transform data from multiple sources into our data platform.
  • Collaborate with analysts and stakeholders to understand data requirements and ensure data availability for reporting and analytics.
  • Support the integration of structured and unstructured data from internal and external sources.
  • Ensure data quality, consistency, and integrity by implementing validation and monitoring processes.
  • Optimize database queries and pipeline performance for efficiency and scalability.
  • Document data workflows, processes, and best practices for repeatability and transparency.
  • Participate in troubleshooting, debugging, and resolving data pipeline issues in a timely manner.
  • Stay updated on emerging data engineering tools and practices to improve workflows.

Requirements

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field (or equivalent practical experience).
  • Basic experience with SQL and at least one programming language (Python preferred).
  • Familiarity with ETL concepts, data modeling, and relational databases.
  • Exposure to cloud platforms (Azure, AWS, or GCP) is an advantage.
  • Strong analytical and problem-solving skills with attention to detail.
  • Eagerness to learn, adapt, and grow in a fast-paced environment.
  • Experience with data pipeline/orchestration tools (e.g., Airflow, Prefect).
  • Familiarity with distributed data frameworks (e.g., Spark, Hadoop).
  • Knowledge of data visualization tools (Power BI, Tableau) to support downstream consumers.

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