Data QA Engineer

28/09/2026
VND 45,000,000 / tháng

Tổng quan công việc


  • Ngày đăng
    28/09/2026
  • Ngày hết hạn
    30/11/2026
  • Kinh nghiệm
    , 8+ năm
  • Bằng cấp
    Cử nhân
  • Trình độ
    Senior
  • Loại công ty
    Outsourcing
  • Kiểu làm việc
    Remote
  • Quốc gia
    Vietnam
  • Domain
    Banking / Finance / Fintech
  • Thời gian làm việc
    T2 - T6 (VN)
  • Địa điểm làm việc
    Remote, Vietnam
  • Mức lương
    VND 45,000,000 / tháng

Mô tả công việc

  • Working time: Mon to Fri. From 2pm – 11pm (VNT)
  • Location: Remote working, based in Viet Nam
  • Contract duration: 6 months (possibly extend)
  • Domain: Insurance
  • Client Nationality: EU
  • Salary: 45M net (no SHUI, open for 2nd job)
  • Interview process: 4-5 rounds
    • 1-2 rounds with VN team (HR round +  Technical round)
    • 3 round Client (English language verification test + Technical verification with Poland team + Final round with UK team)
  • English requirement: Fluent (C1), working directly with the client-side engineering team

DESCRIPTION

The client operates in the insurance sector and is delivering a strategic technology transformation program focused on building a modern, scalable cloud-based data platform. The project involves migrating existing processes from a legacy .NET environment to a new data & analytics platform within the Microsoft ecosystem. A key objective of the initiative is ensuring high data quality, reliability of ETL processes, and integration with multiple partner and downstream systems.

TECHNICAL REQUIREMENTS

Must Have

• Fabric knowledge

• Strong SQL

• Data and ETL testing experience

• Azure DevOps automation

• Understanding of ADF and OneLake

• Databricks or Synapse experience is also acceptable 

  • Extensive experience as a QA Engineer / Test Engineer (At least 7 years)
  • Experience testing ETL processes and data pipelines.
  • Practical knowledge of end-to-end and regression testing.
  • Experience testing REST APIs.
  • Ability to perform data quality validation (data quality checks).
  • Strong SQL knowledge for data analysis and verification.
  • Experience designing and maintaining automated tests and testing frameworks.
  • Strong test automation experience.
  • Experience validating integration processes and data flows.
  • Ability to analyze logs, monitoring solutions, and identify root causes of defects.
  • Experience working in Agile teams (Scrum).
  • Familiarity with AI-Assisted SDLC practices and tools.

Nice to Have

  • Experience in migration projects (legacy → new platform).
  • Knowledge of cloud-based data & analytics solutions (Microsoft ecosystem).
  • Experience with test automation for data pipelines or APIs.
  • Experience working in highly regulated industries (e.g., insurance or financial services).
  • Experience using AI-supported tools within QA and software delivery processes.

RESPONSIBILITIES

  • Design and execute end-to-end tests for ETL processes, including ingestion, transformation, enrichment, routing, and output layers.
  • Prepare, maintain, and enhance regression tests for data pipelines and API integrations.
  • Design and maintain the quality framework, including automated test coverage, pipeline validation, and regression assurance.
  • Test inbound and outbound API integrations used for communication with downstream systems.
  • Validate data quality, including completeness, consistency, business correctness, and duplicate verification.
  • Verify the correctness of process migrations from legacy systems to the new platform.
  • Analyze logs, monitoring data, and alerts to identify defects, anomalies, and bottlenecks.
  • Collaborate closely with Data Engineers, Architects, and development teams.
  • Participate in defining and enhancing the testing strategy for the data platform.
  • Support QA automation initiatives and promote testing best practices.
  • Leverage AI-assisted tools supporting software quality and delivery processes.
  • Report defects and participate in root cause analysis activities.
  • Contribute to the continuous improvement of quality assurance processes across the project.

ADDITIONAL IMPORTANT INFORMATION

  • Project delivered in an international environment.
  • Opportunity to work on a modern enterprise data and integration platform within the Microsoft ecosystem.
  • Close collaboration with Data Engineering teams and solution architects.
  • Strong focus on data quality, test automation, and ETL process reliability.
  • Environment supporting AI-assisted software development and quality assurance practices.