Key Responsibilities:

- Design, develop, and maintain ETL/ELT pipelines using Microsoft Fabric.

- Integrate data from multiple enterprise systems into Microsoft Fabric.

- Build, optimize, and manage Lakehouse and Data Warehouse solutions.

- Develop interactive Power BI dashboards, reports, and data visualizations.

- Design and implement AI-powered applications, AI Agents, and chatbots using Azure AI Services and Azure OpenAI.

- Develop scalable data models to support business intelligence and analytics.

- Collaborate with business stakeholders, data architects, and engineering teams to deliver end-to-end data solutions.

- Optimize data pipelines for performance, reliability, and scalability.

- Implement best practices for data governance, security, and DevOps using Git and Azure DevOps.

- Troubleshoot production issues and continuously improve platform performance.

Required Skills & Experience:

- 5-10 years of experience in Data Engineering.

- Strong hands-on experience with:

1. Microsoft Fabric

2. ETL/ELT Development

3. SQL

4. Python

5. PySpark

6. Power BI

- Experience building Lakehouse and Data Warehouse solutions.

- Hands-on experience with Azure AI Services and Azure OpenAI.

- Strong understanding of Data Modeling and enterprise data architecture.

- Experience with Git, version control, and Azure DevOps.

- Strong analytical, troubleshooting, and problem-solving skills.

Preferred Skills:

- Exposure to Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI Agent development.

- Experience with Azure Data Factory, Synapse Analytics, or Databricks.

- Familiarity with CI/CD pipelines and cloud-native data platforms.

Key Competencies:

- Microsoft Fabric

- Data Engineering & ETL/ELT

- SQL, Python & PySpark

- Power BI

- Azure AI Services & Azure OpenAI

- Data Modeling & Lakehouse Architecture

- AI Agents & Generative AI

- Git & Azure DevOps

- Cloud Data Platforms

- Stakeholder Collaboration & Problem Solving