We are seeking a highly skilled
Data Engineer with strong expertise in
AI-driven solutions and Microsoft Azure infrastructure to join our team in Singapore. The ideal candidate will bring both
data engineering and data science background, with proven experience in
Copilot Studio, RAGs (Retrieval Augmented Generation), and AI Foundry implementations.
Key Responsibilities
- Design, build, and optimize data pipelines and workflows to support AI and analytics initiatives.
- Work hands-on with Copilot Studio for AI-driven application development and automation.
- Implement AI Foundry solutions on Microsoft Azure, ensuring scalable, secure, and cost-effective architecture.
- Develop and deploy RAGs (Retrieval-Augmented Generation) solutions for enterprise AI use cases.
- Collaborate with data scientists, solution architects, and business stakeholders to deliver AI-enabled data products.
- Manage and optimize data storage, integration, and retrieval strategies across structured and unstructured data sources.
- Ensure best practices in data governance, security, and compliance within Azure cloud infrastructure.
Required Skills & Experience
- 7-8 years of proven experience as a Data Engineer or AI/ML-focused Data Engineer.
- Strong background in data science, data engineering, and machine learning concepts.
- Hands-on expertise in Microsoft Azure services (Data Factory, Databricks, Synapse, Cognitive Services, AI Foundry, etc.).
- Practical implementation experience with Copilot Studio.
- Proven experience in RAGs (design, creation, and deployment).
- Strong programming/scripting knowledge (Python, SQL, PySpark, etc.).
- Experience with ETL/ELT, data warehousing, and API integrations.
- Good understanding of MLOps and AI deployment frameworks.
- Strong problem-solving skills, ability to work in fast-paced environments, and excellent communication skills.
Preferred Qualifications
- Microsoft Azure certification(s) such as DP-203, AI Engineer Associate, or Azure Solutions Architect.
- Experience with large-scale AI implementations in enterprise environments.
- Exposure to vector databases and LLM integration for AI-powered search and analytics
