This role will follow a hybrid working arrangement with our client, 3 days per week onsite in the Nonthaburi area. High possibility to be converted to our full time engineer.
In this role, you will get to:
- Design and build scalable, reliable data pipelines (ETL/ELT) for large-scale datasets
- Architect and implement modern data platforms using Databricks (Lakehouse, Delta Lake)
- Develop robust data processing using Python (PySpark) and SQL
- Own end-to-end data workflows: ingestion, transformation, validation, serving
- Optimize data pipelines for performance, scalability, and cost efficiency
- Define and enforce data engineering best practices, standards, and governance
- Collaborate with Data Scientists, Analysts, and Product teams to translate business needs into data solutions
- Implement orchestration and scheduling frameworks (e.g., Airflow / Databricks Workflows)
- Ensure data quality, reliability, and observability across pipelines
- Lead technical discussions and contribute to architecture decisions
- Mentor junior engineers and support team capability building
You’ll be successful if you have:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field
- 4+ years of hands-on experience in data engineering roles, ideally using Databricks in building scalable data pipelines
- Expertise in building data pipelines using tools like Databricks, Airflow
- Strong knowledge of data lake/warehouse architecture (e.g., Snowflake, Redshift, BigQuery, or Delta Lake)
- Advanced in Python, SQL programming skills
- Proven experience working with cloud infrastructure (AWS, GCP, Azure) and managing cloud-native data platforms
- Strong problem-solving and communication skills; able to lead data initiatives with minimal supervision
- Good command in English
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