Data Engineer (80 - 150K) at Kate… · Bangkok

HIRING POSITION: Data Engineer (Open to Thai Nationals Only )

WORKING CONDITION: On-site and Hybrid with Future 4-day work week

LOCATION: BANGKOK, THAILAND (MRT Accessible)

PAY RATE: UP TO THB 150000

We're in search of a dynamic Data Engineer to join our team, bringing expertise and innovation to the table. Your pivotal role involves constructing and maintaining data pipelines that power our Artificial Intelligence (AI) and Large Language Model (LLM) projects. From data ingestion to transformation and preparation for AI model training and deployment, you'll be at the forefront of our data endeavors.

Responsibilities:

• Develop and maintain data pipelines for AI/LLM projects, ensuring efficiency and reliability.
• Leverage cloud platforms such as AWS, GCP, or Azure for seamless data storage, processing, and analytics.
• Collaborate with various data sources including databases, APIs, and sensors, extracting and transforming data for analysis.
• Conduct data cleansing and preprocessing to optimize datasets for machine learning algorithms.
• Implement robust data quality checks and monitoring mechanisms.
• Work closely with data scientists and ML engineers to grasp modeling requirements.
• Document data pipelines meticulously and uphold code maintainability standards.
• Stay abreast of cutting-edge big data technologies and tools like Spark, Hadoop, and Kafka.

Qualifications:

• Minimum 3 years of experience in Data Engineering or a related field.
• Sound grasp of data engineering principles and best practices.
• Proficiency in scripting languages such as Python or Java, along with SQL expertise.
• Familiarity with cloud platforms (AWS, Huawei GCP, Azure) for effective data management.
• Experience with big data processing frameworks like Spark and Hadoop.
• Understanding of machine learning concepts and data preparation techniques.
• Proficiency with data versioning and management tools like Git.
• Strong problem-solving and analytical abilities.
• Excellent communication and collaboration skills.

Bonus Points:

• Hands-on experience with machine learning libraries like TensorFlow or PyTorch.
• Experience in building and deploying AI/LLM models.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Exposure to infrastructure automation tools like Terraform or CloudFormation.