Data Engineer (Microsoft Fabric & API Integration)
Singapore-based Data Engineer building and maintaining enterprise data platforms on Microsoft Fabric. Day to day: developing scalable ETL/ELT pipelines (Data Factory, Dataflows, Notebooks, Lakehouse), integrating ERP/CRM and external systems via REST/SOAP APIs, and supporting data governance, monitoring, and reporting/analytics.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Degree in Computer Science, IT, Data Engineering, or related discipline
- 3-5 years of experience in Data Engineering or Data Integration
- Hands-on experience with Microsoft Fabric (Data Factory, Dataflows, Notebooks, Lakehouse, Data Warehouse)
- Experience building ETL/ELT pipelines and enterprise data integration solutions
- Good knowledge of SQL and data modelling principles
- Experience integrating systems via RESTful APIs, SOAP services, and enterprise interfaces
- Familiarity with authentication methods (OAuth2, JWT, API Keys)
- Understanding of data governance, metadata management, and data lineage
- Experience with Agile delivery methodologies
- Strong analytical, troubleshooting, and communication skills
Full description
Job Overview
We are looking for an experienced Data Engineer to build and support enterprise data platforms using Microsoft Fabric . This role will focus on developing scalable data pipelines, integrating multiple business systems, and delivering reliable data solutions that support reporting, analytics, and business operations.
The ideal candidate should have hands‑on experience with cloud data platforms, ETL/ELT development, API integrations, and enterprise data architecture.
Key Responsibilities
Data Engineering & Integration
- Develop and maintain scalable data pipelines using Microsoft Fabric.
- Build data ingestion processes from ERP, CRM, databases, cloud applications, and external platforms.
- Design and implement ETL/ELT solutions using Fabric Data Factory, Dataflows, Notebooks, and Lakehouse.
- Develop efficient data models to support reporting, dashboards, and analytics.
- Ensure data accuracy through validation, reconciliation, and quality controls.
API & System Integration
- Develop integrations using RESTful APIs, SOAP services, and enterprise interfaces.
- Automate data extraction and synchronization between internal and external systems.
- Configure authentication methods such as OAuth2, JWT, and API Keys.
- Troubleshoot and optimize API connectivity and performance.
- Ensure secure and reliable data exchange in line with enterprise security standards.
Data Architecture & Governance
- Support enterprise data architecture and integration initiatives.
- Implement metadata management, data lineage, and governance practices.
- Design scalable data storage solutions using Lakehouse and Data Warehouse technologies.
- Contribute to master data management and enterprise data standards.
Performance & Support
- Monitor and optimize data pipelines for performance and reliability.
- Implement logging, monitoring, and alerting mechanisms.
- Investigate production issues, perform root cause analysis, and implement long‑term solutions.
- Prepare technical documentation and provide knowledge transfer to support teams.
Collaboration
- Work closely with business users, data architects, business analysts, and application teams.
- Participate in Agile development activities, sprint planning, and design discussions.
- Gather technical requirements and recommend appropriate data integration solutions.
Requirements
- Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
- At least 3 to 5 years of experience in Data Engineering or Data Integration.