Data Engineer

CÔNG TY CỔ PHẦN GEM

Thỏa thuận
30/04/2026
Toàn thời gian
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
  • Salary: Up to 50M;
  • Probation salary is 100% of the official salary;
  • 13th-month salary and performance review twice a year;
  • Bonus for special occasions each year (Labor Day, National Day, Solar New Year, Lunar New Year);
  • Enjoy the company summer trip and other team-building activities held monthly and quarterly;
  • IT Certificate allowance as regulated;
  • Social, health and unemployment Insurance following the government policy;
  • Health Care Insurance;
  • Professional, creative and dynamic working environment;
  • Work five days per week from Monday to Friday with a flexible check-in time.
CONTACT
  • Send CV to: [protected info]
  • Hotline: +[protected info] (Recruitment Team)
  • Facebook GEM Careers: [protected info]
  • LinkedIn GEM Careers: [protected info]

Thông tin chung

  • Thu nhập: Thỏa thuận

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