Microsoft Fabric - Data Engineer

Cognizant Romania is home to 2300+ creative technologists and is one of Eastern Europe's largest Software Product Engineering delivery networks. We serve global clients in several industries, including Banking & Financial Services, Insurance, Healthcare & Life Sciences, Communication Media & Technology, and Retail & MLEU (manufacturing, logistics, energy & utilities).

Cognizant Romania was established in 2018 when Cognizant acquired Softvision, a company founded in the late 1990s in Cluj-Napoca, Romania. We continue to build on our history as the preferred engineering partner for thriving Silicon Valley tech companies, now as a prominent Cognizant next generation studio.

About the role:

The role is responsible for the design, development, and maintenance of scalable data solutions using Microsoft Fabric.

The role focuses on building end-to-end data pipelines, working with business users and technical teams to deliver analytics-ready datasets using Agile principles.

The role requires strong expertise in Fabric data engineering capabilities, applying both technical and business knowledge to develop robust, performant, and governed data solutions.

The role holder is expected to:

• Collaborate with business users and technical teams to understand requirements
• Design and implement data ingestion, transformation, and delivery pipelines
• Ensure performance, and scalability of solutions
• Apply a structured and timely approach to delivery with high quality standards
• Demonstrate strong analytical and problem-solving skills

Responsabilities:

• Design, develop and maintain data pipelines within Microsoft Fabric
• Build and optimise ETL/ELT processes for analytics consumption
• Develop and maintain Fabric Dataflows, Lakehouse and Warehouse
• Ensure data is accessible, reliable and governed across platforms
• Optimise performance and cost of data platforms
• Work within Agile teams and participate in sprint ceremonies

Technical Skills:

• Microsoft Fabric (Dataflows, Lakehouse, Warehouse)
• Azure Data Services (Synapse, Data Factory, Data Lake)
• SQL (advanced) and Python/Spark for data transformation
• Strong understanding of data modelling (e.g. star schema)
• Experience building scalable data pipelines for large datasets
• Experience in financial services data environments (desirable)