Role Summary
We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and
infrastructure that support analytics, AI/ML, and business intelligence use cases for BankX’s digital
banking platform.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines for batch and real-time data processing.
- Build and optimize data ingestion, transformation, and loading (ETL/ELT) workflows.
- Work with Azure Data Services, Databricks, and Delta Lake to implement Lakehouse architecture.
- Ensure data quality, reliability, and availability across all data products.
- Collaborate with Data Architects to implement data models and architecture standards.
- Support data governance, metadata management, and lineage tracking.
- Ensure pipelines comply with PDPA, data classification, and security requirements.
- Monitor pipeline performance and troubleshoot data issues in production environments.
- Work closely with Data Scientists and Analysts to deliver model-ready datasets.
- Participate in code reviews and promote engineering best practices.
Qualifications & Preferred Skills
Required:
- 4+ years of experience in data engineering or related roles.
- Strong proficiency in SQL and Python for data transformation and processing.
- Hands-on experience with Azure Data Services, Databricks, and Delta Lake.
- Experience building and maintaining ETL/ELT pipelines at scale.
- Familiarity with data modeling concepts and distributed data systems.
- Understanding of data governance, data quality, and security practices.
- Proficient in Thai and English at intermediate level or above, sufficient for technical discussions,
meetings, and written documentation
Preferred:
- Experience in banking, fintech, or other regulated industries.
- Knowledge of streaming technologies such as Apache Kafka or Azure Event Hubs.
- Familiarity with CI/CD practices and infrastructure-as-code for data pipelines.
- Exposure to Unity Catalog, Azure Purview, or similar metadata management tools.
- Experience working in Agile/Scrum environments.