Principal, Data Engineer

Data | Hồ Chí Minh | Full-time

We are seeking Principal, Data Engineer to join our data platform team. The data platform team is responsible for maintaining the current data analytics infrastructure as well as overseeing thedesign and development of future products to enable AI, automation, and innovative analytics. This team will be focusing on developing our advanced algorithms to make proven business impacts and developing any tools or processes required to do so. The Manager Data Engineer will focus on continuously upgrading the data system (data infrastructure, MLOps, engagements) to resolve the business problem and data-driven business purposes. Developing complex data infrastructure and managing architecture and code will be crucial in driving the organization‘s data strategy and enabling data-driven decision-making. He/she is also responsible for the development and launch of data products. This role will require a strong understanding of data technology, data infrastructure, containerize and MLOps systems. The ideal candidate will be able to work effectively with cross-functional teams to bring data-driven products to market.

Data Technology and Infrastructure Expert: In-depth know-how of different kinds of data technologies, data standard, data operations and data infrastructure development.

Optimizer: Make sure the most complex data architecture run at the lowest cost.

Development Principal: Give principles to the analytics engineer to follow, make sure architecture and code are clean, easy to follow and easy to fix.

Analytics Expert: Principal data engineer requires an understanding of data analysis principles and formulas. Possessing data analysis skills allows you to create effective, accurate and concise models that communicate the information and meaning of a dataset.

Data Translator: Highly effective communicators who can transform data findings into recommendations to compose reports and executive-level presentations.

Data Platform Builder: Data engineering skills & Data modelling, Using software development best practices like code review, continuous integration, and continuous delivery (CI/CD), release management, and version control. Also build and maintain the MLOps system.

What you’d contribute:

  • Maintain and enhance current data analytics infrastructure while designing and developing future products for AI, automation, and innovative analytics.
  • Develop advanced algorithms to drive business impact and create necessary tools or processes.
  • Continuously upgrade data systems to address business challenges and enable data-driven decision-making.
  • Drive the organization‘s data strategy, manage architecture and code, and launch data products.
  • Build and maintain Data Lake, Data Mart, and Data Warehouse with the Data Engineering team.
  • Enhance Feature Stores and Data Enrichment processes.
  • Provide clean, transformed data for analysis and modeling.
  • Maintain data documentation and definitions.
  • Develop and manage data platform including MLops and DataOps.
  • Collaborate with cross-functional teams to define business goals and measure analytics outcomes.
  • Design data models, develop data pipelines, and manage data storage systems.
  • Create documentation for data pipelines and storage systems.
  • Troubleshoot and debug data system errors.
  • Stay updated with industry best practices and new technologies for continuous improvement.

 

What you’d have to succeed for the role:

  • Strong expertise in data technologies, operations, and infrastructure development.
  • Ability to optimize complex data architecture for cost efficiency.
  • Provide guidance on architecture and code cleanliness for analytics engineers.
  • Proficient in data analysis principles and formulae to create effective and concise models.
  • Strong communication skills to transform data findings into actionable recommendations.
  • Skilled in data engineering, modeling, and software development best practices.
  • Proficient in SQL, Python/R/Scala, DataOps tools (e.g., Docker, Kubernetes), and cloud platforms like GCP.
  • Understanding of business architecture in analytics, preferably in Retail/E-commerce.
  • Efficient problem-solving and analytical skills.

 

What we love to offer:

  • Hybrid working
  • Attractive package + immediate healthcare insurance
  • Full paid during the probation period
  • Social insurance contributions paid on full salary
  • Be coached by experienced & inspirational leaders and managers
  • Tech application of autonomous robots and AI technologies
  • Unlimited access to knowledge via learning library & via team knowledge-sharing

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