We are looking for a team of Data Engineers to join our Insurance/Financial Services Projects. 

This role focuses on building and maintaining scalable data pipelines and supporting Data Analytics initiatives. The ideal candidate should have strong hands-on experience in data processing, transformation, and data modeling, while being able to collaborate closely with Data Analysts and Business stakeholders. 

The role requires an understanding of data engineering fundamentals with a practical orientation toward enabling analytics and reporting use cases.

LOCATION: HCMC

JOB DESCRIPTION  

1. Data Pipeline Development

• Design, build, and maintain ETL/ELT pipelines; 
• Develop batch and/or near real-time data processing workflows; 
• Integrate data from multiple internal and external sources; 
• Ensure data accuracy, consistency, and reliability.

2. Data Modeling & Transformation

• Design data models to support reporting and analytics; 
• Develop transformation logic for structured and semi-structured datasets; 
• Optimize data warehouse schemas (star schema, snowflake schema, etc.). 

3. Analytics Enablement

• Work closely with Data Analysts to understand reporting needs; 
• Prepare curated datasets for dashboards and BI tools; 
• Support data validation and quality checks. 

4. Data Quality & Governance

• Implement data validation and monitoring mechanisms; 
• Ensure compliance with financial/insurance data governance standards; 
• Maintain proper documentation for data flows and architecture. 

5. Performance Optimization

• Optimize SQL queries and pipeline performance; 
• Improve cost efficiency for cloud-based data platforms. 

REQUIRED SKILLS AND EXPERIENCE 

1. Core Data Engineering

• Strong SQL skills (query optimization, complex joins, window functions); 
• Experience with ETL/ELT tools (e.g., Airflow, DataStage, SSIS, or similar); 
• Experience working with relational databases (Oracle, MySQL, PostgreSQL, SQL Server); 
• Understanding of data warehouse concepts; 
• Experience working with large datasets; 
• Proficiency in Python (for data processing).

2. Analytics Collaboration

• Understanding of BI tools (Power BI, Tableau, etc.); 
• Ability to work closely with Data Analysts. 

3. Experience & Soft Skills

• 3–5 years of experience in Data Engineering; 
• Strong analytical mindset; 
• Good communication skills (English required for client communication); 
• Ability to work in Agile/Scrum environment; 
• Detail-oriented and quality-focused. 

PREFERRED SKILLS

1. Technical Skills 

• Experience with Azure (Data Factory / Synapse); 
• Experience with AWS (Glue, Redshift, S3, Lambda); 
• Experience with GCP (BigQuery, Dataflow); 
• Familiarity with Spark or similar distributed processing frameworks; 
• Experience in enterprise-scale data platforms; 
• Exposure to data governance frameworks; 
• Knowledge of CI/CD for data pipelines; 
• Experience in handling sensitive financial/customer data. 

2. Domain Knowledge

• Experience in Insurance or Financial Services; 
• Understanding of policy, claims, underwriting, or customer data; 
• Familiarity with compliance and data privacy standards. 

 BENEFITS