Fabric Data Engineer (1-year contract)
Savills Vietnam Ho Chi Minh City, Vietnam
Real Estate · 1,001-5,000 employees
About the role
The Fabric Data Engineer will design, develop, and optimize enterprise data solutions, including building robust ETL/ELT pipelines across cloud and on-premises platforms. They will also partner with business stakeholders to translate requirements into scalable data engineering deliverables and maintain technical documentation.
What they look for
Requirements
Candidates must have at least 3 years of experience in leading enterprise data solution design and implementation. A bachelor's or master's degree in a relevant field such as Information Technology or Computer Science is required.
Full description
Scope:
The Fabric Data Engineer will lead the design, development, integration and optimisation of enterprise data solutions across cloud and on-premises platforms. The role is responsible for building robust ETL/ELT pipelines, managing structured and semi-structured data assets, supporting analytics and reporting outcomes, and partnering with Business Analysts and stakeholders to translate business needs into secure, scalable and supportable data engineering solutions.
Key Responsibilities
- Own the structuring, development and ongoing management of in-house data construction, data integration and data management activities.
- Design, build and enhance ETL/ELT pipelines across multiple data sources using technologies such as Microsoft Fabric, SSIS, Azure Data Factory and Azure Functions / Function App.
- Integrate, transform and analyse data from relational, cloud and NoSQL platforms, including Azure SQL, Azure Blob Storage and MongoDB.
- Partner with Business Analysts, application teams and business stakeholders to understand technical and business requirements and convert them into data engineering deliverables.
- Develop and maintain data models, database objects, stored procedures and reusable data transformation logic using SQL and relevant programming languages.
- Implement data quality checks, reconciliation controls, performance tuning and exception handling to improve reliability and operational stability.
- Participate in end-to-end project delivery using hybrid and agile delivery methodologies, including estimation, solution design, build, testing, deployment and hypercare.
- Support reporting and analytics platforms such as Microsoft Fabric and SSRS by enabling trusted, governed and fit-for-purpose datasets.
- Prepare and maintain technical documentation, data lineage details, operational runbooks and knowledge transfer materials for BAU support.
- Provide technical guidance, troubleshooting and root-cause analysis for complex production data issues.
Domain Experience
- Prior experience as a Data Engineer or in a similar senior technical data role.
- Experience in one or more relevant domains such as CRM, Big Data, Business Intelligence, analytics reporting, enterprise data integration or data management.
- Exposure to stakeholder-facing delivery where technical solutions must be aligned to business outcomes.
- This senior position emphasises building ETL/ELT pipelines, managing diverse data platforms and collaborating closely with business stakeholders to deliver scalable data engineering solutions
Experience & Qualifications
- Bachelor's or master's degree in information technology, Computer Science, Engineering, Data Science or a related discipline.
- Data engineering, cloud or Microsoft technology certifications will be an advantage
- 3+ Years of experience in leading enterprise data solution design and implementation experience across cloud and on-premises systems.
Skill Area
Expected Capability
Priority
- Data Engineering: ETL/ELT design, data transformation, data modelling, data mining and segmentation techniques.
- Microsoft Cloud Data Stack: Azure Data Factory / Data Pipeline, Dataflows Gen2, SSIS, Azure Functions / Function App, Azure SQL, Azure Blob Storage and Microsoft Fabric.
- Database & Querying: Strong SQL skills, database design, performance tuning and hands-on experience with relational database platforms.
- Programming: Working knowledge of Python (Notebook - PySpark) and C# for data processing, automation and integration use cases.
- Reporting & Analytics: Experience with SSRS and exposure to BI / analytics reporting environments.
- Data Platforms: Experience with NoSQL and cloud-based storage or data platforms.
- Delivery Methods: Knowledge of end-to-end project delivery, hybrid and agile ways of working.
- Certifications: Relevant data engineering, cloud, Microsoft Fabric or Azure certifications.
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