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Senior Data Engineer

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Onsite

Senior Data Engineer

MIRAE ASSET

Senior Data Engineer

Skills

SQL QueriesData EngineeringPythonData AnalysisMachine LearningAIdbtOraclePySparkApache Airflow

2 months ago

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Important information


Location:

Ho Chi Minh City, Vietnam

Work mode:

Onsite

Published on:

21 August 2026

What they need


Nơi làm việc

  • Hồ Chí Minh (Quận 1)

Cấp Bậc

  • Nhân viên

Hình Thức

  • Nhân viên chính thức

Bằng Cấp

  • Đại học

Kinh Nghiệm

  • 3 - 6 Năm

Mức Lương

  • Lương thỏa thuận

Ngành nghề

  • CNTT - Phần mềm,Tài chính / Đầu tư

Phòng Ban

  • CNTT và Phân tích dữ liệu

Hạn chót nhận hồ Sơ

  • 30/10/2026

Người Liên Hệ

  • Ms Trang

Mô tả công việc

  • Develop ETL/ELT jobs to ingest, transform, and load data from multiple source systems into Data Warehouse / Data Lake platforms based on the approved analysis and design documents.
  • Hands-on experience in building and maintaining ETL/ELT pipelines, especially using Oracle Data Integrator (ODI) or Airflow. Troubleshoot and optimize data pipelines to improve scalability, performance, and operational efficiency.
  • Utilize jobs, workflows, APIs and streaming to manage large-scale data processing workloads.
  • Support ML/AI initiatives through data preparation, exploratory analysis, and metric definition.
  • Design and optimize data models, data marts, and data warehouse structures to support analytics and reporting.
  • Ensure data quality, governance, reliability, and performance across enterprise data platforms.
  • Mentor a team of engineers while driving best practices in data modeling and system design for data-heavy applications.

Yêu cầu công việc

  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related fields.
  • Minimum 3+ years in data engineering across large/complex datasets and operate pipelines at scale and integrating multiple source systems.
  • Solid background in Data engineering best practices.
  • Strong skills in dbt, Python, PySpark, Spark streaming and Advanced SQL.
  • Understanding and hands-on exposure to DataOps practices, including CI/CD for data pipelines, monitoring, logging, and data quality automation.
  • Experience with Git and modern software development practices is a plus

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