Senior Data Engineer

Job Description

What you’ll need to succeed

• Design and build scalable data models — design and develop well-structured facts, dimensions, and semantic layers using PySpark, Synapse, Fabric Lakehouse/Warehouse, and Power BI, ensuring alignment with business and analytical requirements.
• Develop ingestion and transformation pipelines — design and implement end-to-end data ingestion frameworks in Synapse Pipelines and Data Factory to source data from APIs, databases, and files. Build efficient ELT frameworks in Synapse and Fabric to integrate and transform large, complex datasets.
• Design and deliver BI and analytics solutions — create Power BI models and reports that enable trusted analytics and actionable insights.
• Optimize and govern — ensure high performance, cost efficiency, and data quality across Spark, SQL, and Fabric workloads through effective design and governance practices.
• Collaborate and lead — partner with architects, analysts, and business stakeholders to design end-to-end data products, while mentoring engineers and promoting best practices in data design and delivery.
  
  Selection Criteria:
• 5 years+ experience working in Analytics or data warehousing environments
• Expert in data warehousing, data modelling, and end-to-end business intelligence solutions using Power BI, SQL, DAX.
• Expert level knowledge in PySpark, SQL. Hands-on Synapse, Fabric (Spark + Pipelines).
• Strong background in lakehouses, data platform frameworks and data mesh architecture
• Experience with Azure Devops, branching and pipelines
• Experience delivering data solutions in projects with big data volumes

Are you interested in this position?

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