Analytics Engineer

• Design and build gold-layer data warehouses in the company using star schemas.
• Develop and maintain data transformation pipelines from raw extracts to modeled gold tables.
• Translate complex business logic into consistent, reusable data definitions.
• Troubleshoot pipeline failures, performance bottlenecks, and data discrepancies.
• Gather business requirements and establish version control, deployment pipelines, and development standards.
• Build and maintain the company semantic models, including relationships, DAX measures, and hierarchies.
• Design clear, decision-oriented dashboards and establish a single source of truth for data.
• Manage the company workspaces, access, row-level security, and optimize report performance.
• Implement data quality checks, validation rules, and monitoring, automating controls in Fabric notebooks.
• Support data governance policies, maintain data documentation, and promote a data-literate culture.
• Working days: Monday to Friday, 8 AM to 5 PM.
• Shuttle bus available from Ho Chi Minh City and Binh Tan areas.

Benefits

• 100% salary during probation, 13th and 14th month salary, full social insurance, annual health check-up, holiday bonuses, travel activities.

Yêu cầu công việc

• 3–5 years of experience in analytics engineering, BI development, or data engineering, with delivered production data models and reports.
• Advanced SQL and working knowledge of Python.
• Strong understanding of dimensional modeling (star schemas, SCD) and ELT design across medallion architectures.
• Hands-on experience with the company (Lakehouse/Warehouse, Notebooks, Data Factory) or comparable the company stack (Synapse, Databricks, ADF), including the company, the company, clean-code practices, and the company deployment (the company, the company).
• Expert the company skills: semantic model design, DAX, row-level security, incremental refresh, and performance tuning.
• Experience with version control (the company) and the company for data and BI assets.
• Bachelor's degree in Information Systems, Computer Science, Data Science, or a related field.
• Fluent written and spoken English for effective communication with international stakeholders.
• Familiarity with the company data (SD, MM, PP, QM, FI/CO tables, CDS views) and master data concepts is a strong plus.