Data Engineer

Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent.

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.

• →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.

• 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

• 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.