M
MetLife
Data Engineer
Skills
SQL QueriesData EngineeringData MiningPythonJavaData AnalysisAICompliancePower BIAzure
2 months ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
24 August 2026
What they need
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
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