Microsoft Fabric AI Implementation Engineer

Role Summary:

We are seeking a Microsoft Fabric AI Implementation Engineer to design and implement modern data and AI solutions using Microsoft Fabric. The role focuses on building AI-ready data models, enabling Microsoft Fabric AI use cases, and delivering trusted business insights through Power BI and conversational analytics.

Key Responsibilities:

- Design and implement data solutions using Microsoft Fabric components including Lakehouse, OneLake, Data Pipelines, Notebooks, and Semantic Models.

- Develop AI-ready data models that support business KPIs, analytics, reporting, and natural language querying.

- Implement AI solutions leveraging Microsoft Fabric Data Agents and Fabric AI capabilities.

- Create and maintain Power BI dashboards, reports, datasets, and semantic models.

- Collaborate with business users and technical teams to gather requirements and translate them into practical data and AI solutions.

- Support conversational analytics use cases and self-service business intelligence initiatives.

- Ensure data governance, security, access control, and compliance best practices are implemented.

- Design proof-of-concepts (POCs) and minimum viable products (MVPs) for AI and analytics solutions.

- Optimize data models and reporting solutions to ensure performance and scalability.

- Support continuous improvement of the organization's Data & AI capabilities within Microsoft Fabric.

Tech Stack:

- Microsoft Fabric, Lakehouse, OneLake, Data Pipelines, Notebooks, Semantic Models

- Python, SQL, PySpark

- Power BI, DAX, Conversational Analytics

- Generative AI (GenAI), LLMOps, Fabric Data Agents

- Snowflake AI/ML

Experience & Qualifications:

- 5 - 8 years of experience in Data Engineering, Analytics Engineering, AI Engineering, or related domains.

- Hands-on experience with Microsoft Fabric Data Engineering capabilities.

- Experience implementing AI use cases using Microsoft Fabric AI services.

- Strong experience in Power BI, semantic modeling, and dashboard development.

- Proficiency in SQL and Python/PySpark.

- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field preferred.