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About This Job

Work Location

  • Ha Noi

Job Level

  • Experienced (Non - Manager)

Job Type

  • Permanent

Experiences

  • 5 Years

Salary

  • Negotiable

Industry

  • Insurance, IT - Software, Banking, Finance / Investment

Deadline to Apply

  • 31/03/2026
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Job Benefit

  • Laptop
  • Insurance
  • Travel opportunities
  • Allowances
  • International Travel Opportunity
  • Uniform
  • Incentive bonus
  • Health checkup
  • Training & Development
  • Salary review
  • Business Expense
  • Annual Leave
  • Sport Club

Job Description

  • Design Data Warehouse/Data Lake/Data Lakehouse architectures to meet analytics and big data processing requirements while maintaining data infrastructure.
  • Build, optimize, and monitor ETL/ELT pipelines (batch and streaming) to collect and process data from multiple sources.
  • Integrate data from various sources (DB, API, Cloud services, IoT, etc.).
  • Implement high-performance data storage solutions (Snowflake, BigQuery, Redshift, Hadoop, Spark).
  • Ensure data security, integrity, and compliance with regulations (GDPR, ISO 27001, etc.).
  • Optimize query performance while maintaining data integrity and security.
  • Support Data Analysts and Data Scientists by providing clean, complete, and timely datasets.
  • Propose improvements to data infrastructure for cost efficiency and performance optimization.

Job Requirement

  • Bachelor’s degree in IT, Data Science, or related fields.
  • Minimum 5 years of experience in Data Engineering or Backend development with a focus on data processing.
  • Advanced proficiency in SQL and at least one programming language for data processing (Python, Scala, or Java).
  • Hands-on experience with ETL/ELT tools (Airflow, Talend, dbt, etc.).
  • Experience with distributed data processing systems (Spark, Flink, Kafka).
  • Experience working with real-time data (Kafka, Spark Streaming).
  • Experience deploying data pipelines on cloud platforms (AWS/GCP/Azure).
  • Strong understanding of data modeling (star schema, snowflake schema, data vault).
  • Familiarity with data storage systems such as Snowflake, BigQuery, Redshift, or the Hadoop ecosystem.
Job tags: Data Engineer
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