Senior Data Engineer - CP Axtra
CP Axtra (Makro PRO) →Nawamin Road, Bangkok, Thailand
Estimated range. Confirm compensation with the employer.
Nawamin Road, Bangkok, Thailand
Estimated range. Confirm compensation with the employer.
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Listing record updated: October 9, 2026. We archive records after 60 days without an update. This date does not confirm that the employer is still hiring.
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Makro Pro is looking for a Senior Data Engineer to design, implement, and maintain data infrastructure and pipelines. The role involves collaborating with data scientists and analysts to ensure efficient data processing and storage solutions. Key duties include developing scalable data pipelines and ETL processes, optimizing data storage solutions like data warehouses and lakes, and ensuring data quality and consistency. The candidate will also provide technical leadership by mentoring junior engineers and integrating new data technologies.
Design, develop, and maintain scalable data pipelines and ETL processes
Implement and optimize data storage solutions, including data warehouses and data lakes
Collaborate with data scientists and analysts to understand data requirements and provide efficient data access
Ensure data quality, consistency, and reliability across all data systems
Develop and maintain data models and schemas
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
5+ years of experience in data engineering or related roles
Strong programming skills in Python, Java, or Scala
Extensive experience with big data technologies such as Hadoop, Spark, and Hive
Proficiency in SQL and experience with both relational and NoSQL databases
Experience with cloud platforms (AWS, Azure, or GCP) and their data services
Knowledge of data modeling, data warehousing, and ETL best practices
Familiarity with data visualization tools (e.g., Tableau, Power Bl)
Experience with version control systems (e.g., Git) and CI/CD pipelines
Strong problem-solving skills and attention to detail
Stream processing technologies (e.g., Kafka, Flink), machine learning and AI technologies, data governance and compliance requirements, containerization and orchestration tools (e.g., Docker, Kubernetes), open-source projects or relevant certifications, Azure big data platform (ADF, Databrick)
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