Data Engineer

2 weeks ago

Bangkok, Bangkok, Thailand GoPomelo Co., Ltd. Full time

Job Purpose

The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and architectures to support data analytics and machine learning initiatives. This role ensures the efficient collection, storage, and processing of large datasets, enabling seamless data flow and accessibility for business intelligence and decision-making.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines for reliable data flow.
  • Implement ETL (Extract, Transform, Load) processes to integrate data from multiple sources.
  • Integrate structured and unstructured data into databases and cloud environments.
  • Monitor and troubleshoot data integrity to ensure accuracy, consistency, and timeliness.
  • Create, manage, and optimize relational and non-relational databases.
  • Collaborate with data scientists, analysts, and other teams to understand data needs.
  • Maintain clear and up-to-date documentation for data processes and pipelines.
  • Optimize data processing by improving queries, storage, and infrastructure.
  • Automate repetitive tasks to increase efficiency and reliability.
  • Implement Visualization dashboard (Looker Studio)

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Artificial Intelligence, or a related field.
  • 3+ years of experience in Data engineering, Machine learning, AI engineering or a related role, with a strong track record of developing AI models.
  • Experience with AI-driven projects in business applications (e.g., automation, data analytics, recommendation systems).
  • Experience with Data movement (ETL/ELT) projects in business applications (e.g., data analytics, recommendation systems).
  • Proficiency in programming languages such as Python, R, or Java, JavaScript with expertise in machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience with data processing and analysis tools (e.g., Pandas, NumPy, SQL).
  • Solid understanding of machine learning algorithms, deep learning models, and statistical analysis.
  • Familiarity with cloud platforms (AWS, Google Cloud, Azure) and AI services for model deployment and scaling.
  • Strong knowledge of data structures, algorithms, and software development best practices.
  • Experience in version control systems (e.g., Git) and agile development processes.
  • Strong analytical and problem-solving abilities.
  • Excellent communication skills to effectively collaborate with both technical and non-technical teams.
  • Ability to work independently and as part of a collaborative team.
  • Passion for continuous learning and staying up-to-date with the latest AI trends and technologies.

Certifications (Preferred):

  • Data Engineer certifications from recognized platforms (e.g., Google AI, Microsoft Azure AI, TensorFlow, AWS Certified
  • Database Engineer certifications from recognized platforms (e.g., Google AI, Microsoft Azure AI, TensorFlow, AWS Certified
  • Data Science or machine learning-related certifications.

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