Microsoft Fabric Data Engineer

The role of a Microsoft Fabric Data Engineer is to lead the design and development of a scalable, cloud-native data platform on Microsoft Azure while integrating data from various enterprise systems to build a unified data ecosystem.

Responsibilities:

• Design and implement automated data pipelines integrating multiple enterprise systems using Azure technologies.

• Develop efficient data models across diverse business domains to support analytics and AI-driven insights.

• Implement data governance frameworks, optimize pipeline performance, and ensure data security.

• Prepare clean datasets ready for consumption by BI and AI/ML models.

• Document technical details and conduct handover sessions to facilitate knowledge transfer and sustainability.

Must Haves:

• 7+ years of experience in Data Engineering, particularly with Microsoft Azure.

• Strong expertise in Microsoft Fabric, Azure Functions, and Docker Containers.

• Proficient in Python and SQL.

• Experience with Apache Kafka for real-time data processing.

• Understanding of data modeling and multi-source data integration.

Nice to Haves:

• Experience with SAP BW, SAP HANA, and Salesforce.

• Familiarity with CI/CD processes and GitHub.

• Knowledge of data governance and security practices.

• Experience with dimensional and relational data modeling techniques.

Other Details:

• Timezone: CET

• Working Mode: Hybrid (3 days/week in office)

• Location: Koregaon Park Pune

Reason (Must Have):

• 7+ years of experience: This experience ensures the Data Engineer can navigate complex data integration and processing challenges effectively.

• Expertise in Microsoft Fabric: Essential for building a robust Azure-based data ecosystem importantly influencing the success of data integration efforts.

• Proficiency in Python and SQL: These skills are crucial for coding and manipulation of data within the automated pipelines, directly linked to key responsibilities.

Reason (Nice to Have):

• Experience with SAP systems: Valuable for seamless integration of existing enterprise data sources enhancing project outcomes.

• CI/CD knowledge: Benefits the automation of deployment processes, crucial for maintaining efficient data pipelines.