Data Engineer - Microsoft Fabric

We are seeking an experienced Data Engineer with strong expertise in Microsoft Fabric, data ingestion, and cloud-based data integration solutions. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and ingestion frameworks that support batch and real-time data processing., Design, develop, and maintain Microsoft Fabric Pipelines, Dataflows Gen2, notebooks, and Eventstreams.

Build data ingestion solutions using APIs, files, databases, SFTP, batch processing, and streaming technologies.

Develop raw-data landing patterns that preserve source data integrity and retain load, audit, and metadata information.

Implement solutions that support schema evolution, pipeline restarts, data replay, error handling, and failure recovery.

Design secure connectivity using service principals, managed identities, workspace identities, gateways, and appropriate credential-management practices.

Ensure data pipelines are scalable, reliable, secure, and maintainable.

Collaborate with cloud engineering and data platform teams to deliver effective data integration solutions.

Strong hands-on experience with Microsoft Fabric.

Experience developing Fabric Pipelines and Dataflows Gen2.

Proficiency in notebooks and data processing workflows.

Experience with Eventstreams and streaming-based ingestion.

Strong knowledge of API, file, database, and SFTP integrations.

Experience with batch and real-time data ingestion patterns.

Knowledge of raw-data landing zones, metadata management, and schema evolution.

Experience implementing restartability, replay, error handling, and recovery mechanisms.

Understanding of secure authentication and access management, including service principals and managed identities.

Preferred Qualifications

Experience designing enterprise data integration architectures.

Experience with Microsoft Azure cloud services.

Knowledge of data governance, auditing, monitoring, and security best practices.

Experience supporting production data pipelines and troubleshooting ingestion failures.