Senior Data Engineer - Microsoft Fabric

At Accellor, we are a trusted digital transformation partner that uses best-of-breed Cloud technology to deliver superior customer engagement and business effectiveness for clients.

We’ve created an atmosphere that encourages curiosity, constant learning, and persistence. We encourage our employees to grow and explore their interests. We cultivate an environment of collaboration, autonomy, and delegation – we know our people have a strong work ethic and a sense of pride and ownership over their work. They are passionate, eager, and motivated – focused on building the perfect solution but never losing sight of the bigger picture.

We are seeking an experienced Senior Data Engineer for a contract position to design, develop, and optimize data solutions using Microsoft Fabric
. This role requires deep technical expertise in modern data engineering practices and Microsoft's unified analytics platform. Similar experience with Data Bricks would be considered.

• Design and implement scalable data pipelines and ETL/ELT processes within Microsoft Fabric from a code-first approach
• Develop and maintain notebooks, data pipelines, workspace and other Fabric item configurations
• Build and optimize data architectures using delta tables, lakehouse, and data warehouse patterns
• Implement data modelling solutions including star schema, snowflake schema, and slowly changing dimensions (SCDs)
• Performance tune Delta, Spark, and SQL workloads through partitioning, optimization, liquid clustering, and other advanced techniques
• Develop and deploy Fabric solutions using CI/CD practices via Azure Dev Ops
• Integrate and orchestrate data workflows using Fabric Data Agents and REST APIs
• Collaborate with development team and stakeholders to translate business requirements into technical solutions

• Hands-on experience with Fabric notebooks, pipelines, and workspace configuration
• Fabric Data Agent implementation and orchestration
• Fabric CLI and CI/CD deployment practices

• Python (advanced proficiency)
• PySpark for distributed data processing
• Pandas and Polars for data manipulation
• Experience with Python libraries for data engineering workflows
• REST API development and integration

• Delta Lake and Iceberg table formats
• Delta table optimization techniques (partitioning, Z-ordering, liquid clustering)
• Spark performance tuning and optimization
• SQL query optimization and performance tuning

• Visual Studio Code
• Azure Dev Ops for CI/CD and deployment pipelines
• Experience with both code-first and low-code development approaches

• Data warehouse dimensional modeling (star schema, snowflake schema)
• Slowly Changing Dimensions (SCD Type 1, 2,
  3)
• Modern lakehouse architecture patterns
• Metadata driven approaches

• 5+ years of data engineering experience
• Previous experience with large-scale data platforms and enterprise analytics solutions
• Strong understanding of data governance and security best practices
• Experience with Agile/Scrum methodologies
• Excellent problem-solving and communication skills