Senior/Lead Data Engineer

About the Role

This position is being hired on behalf of our client in the digital banking industry.

Your Responsibilities:

• Design, develop, test, deploy, and monitor data pipelines in Databricks on AWS, integrating diverse data sources.
• Design, develop, test, deploy, and monitor scalable code using PySpark and SQL within Databricks.
• Identify and implement process improvements through code optimization and automation.
• Build data quality dashboards, lineage flows, and monitoring tools to ensure active oversight and actionable insights into data quality and governance.
• Assist in migrating data from legacy systems to newly developed solutions.
• Adhere to and champion best practices for data security, retention, and privacy policies.

Requirements:

• Bachelor’s degree.
• 6+ years of experience, with at least 3 years focused on building ETL/ELT pipelines.
• Proven competency in solution design, development, implementation, reporting, and analysis.
• Proficiency in Apache Spark, Python, and SQL.
• Proficiency working with data formats including Text, Delta, Parquet, JSON, CSV, and XML.
• Working knowledge of Spark Structured Streaming.
• AWS infrastructure experience, particularly with S3.
• Solid understanding of Git-based version control, DevOps, and CI/CD practices. Experience with the Atlassian stack is a plus.
• Knowledge of common web API frameworks and web services.
• Strong teamwork, relationship management, and client management skills, with the ability to influence peers and senior management.
• Willingness to embrace modern technology, best practices, and work methodologies.

Benefits:

• Performance-based bonus and equity participation.
• 13th-month salary (pro-rata).
• Generous leave: 15 days annual leave + 3 days sick leave + 1 birthday leave + 1 Christmas leave.
• Meal and parking allowance.
• Full benefits and salary rank during probation.
• Insurances as per Vietnamese labor law and premium health care for you and your family.
• Opportunities for overseas travel for training and work.
• Hybrid work mode, 40-hour work week (Monday to Friday), promoting work-life balance.