Data Engineer - Onsite Quang Trung

- Design, build, and maintain scalable data platforms and pipelines on cloud-based and distributed environments.
- Develop and optimize batch and streaming data pipelines to ensure reliable ingestion, processing, and storage of large-scale datasets.
- Implement and manage data solutions using AWS and Databricks technologies.
- Design and maintain data models (relational, dimensional, and domain-driven) to support analytics and reporting needs.
- Collaborate closely with Data Analysts, Data Scientists, and other stakeholders to translate business requirements into technical data solutions.
- Ensure data quality, reliability, and consistency by applying data validation and quality frameworks.
- Monitor, troubleshoot, and optimize performance of data workflows and distributed systems.
- Enforce security, governance, and compliance standards in regulated environments.

- 2–5+ years of experience in data engineering.
- Strong hands-on skills with:
○ AWS: S3, Glue, Lambda, IAM, Step Functions, Kinesis/MSK
○ Databricks: PySpark, Spark SQL, Delta Lake, Workflows
○ Python & SQL
○ Spark
- Solid understanding of data modeling (relational, dimensional, domain-driven).
- Experience working in large-scale, distributed data environments.

Preferred
- Experience in banking or financial services (core banking, payments, lending, regulatory reporting).
- Familiarity with:
○ Unity Catalog
○ Streaming architectures
○ Terraform or AWS CDK
○ Data quality frameworks (Great Expectations, Deequ, Databricks expectations)
- Experience working in regulated environments with strict compliance and security controls.