Data Engineer

Job description

Description and Requirements

Key Responsibilities

Be responsible for building, enhancing, and maintaining databases in support of applications across the whole IT system Build, maintain, and monitor basic ETL/ELT pipelines from internal and external data sources. Prepare data extraction, transformation, validation, reconciliation, and loading for reporting and analytics needs. Write SQL queries, scripts, and data checks to support data quality, issue analysis, and operational reporting.

Support databases, data marts, data warehouse jobs, and production data processes under guidance from senior engineers. Document data mappings, procedures, issue logs, and support runbooks for continuity and audit readiness. Work with application teams, business analysts, vendors, and reporting users to clarify requirements and resolve data issues. Follow MetLife security, access control, change management, and compliance requirements when handling business data.

Required Qualifications

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Software Engineering, Information Systems, or related field. 1 year of experience in data engineering, ETL support, or data analytics and 2 years of experience in database development/administration, software development. Good SQL foundation and basic understanding of relational databases, joins, views, indexes, and data structures. Basic scripting or programming capability in Python, Java, shell script, or similar language.

Understanding of ETL/ELT, data integration, data validation, and data quality concepts. Strong analytical thinking, attention to detail, learning agility, and clear communication in Vietnamese and English.

Preferred Qualifications

Exposure to tools such as SSIS - (SQL Server Integration Services), or similar. Basic knowledge of cloud data platforms, data lake, data warehouse, or Microsoft Azure services. Experience with Power BI, Excel, or other reporting and analytics tools. Awareness of data governance, data privacy, metadata, lineage, and access control in financial services or insurance.

Competencies and Success Profile Data mindset

Values accurate, complete, secure, and well-controlled data.

Problem solving

Investigates data issues logically and documents findings clearly.

Collaboration

Works effectively with IT, business users, vendors, and regional/global technology teams.

Learning agility

Builds capability in data platforms, cloud tools, and modern engineering practices.

Control orientation

Follows standards, procedures, change controls, and compliance requirements. Preferred and encouraged job holder with AI Readiness, Learning Agility, Digital Mindset