Description
You will design and maintain end-to-end data pipelines using Microsoft Fabric and Azure services, owning the architecture from ingestion to consumption.
Responsibilities
- Build and manage Lakehouse architecture using OneLake, Data Pipelines, Notebooks, and SQL Endpoints.
- Develop scalable ETL/ELT workflows using Python, PySpark, and SQL, including incremental loads, CDC, and watermarking logic.
- Implement data migration from on-premises systems to Azure, ensuring transformation, cleansing, validation, and reconciliation.
- Optimize SQL queries, Spark jobs, and data pipelines for performance while maintaining Bronze, Silver, Gold layers.
- Automate deployments using Azure DevOps CI/CD and monitor production pipelines for reliability.
Required Skills
- 5+ years of experience with Python, PySpark, and SQL.
- Strong proficiency in Microsoft Fabric, including OneLake and Data Pipelines.
- Experience with Azure Data Factory, ADLS Gen2, Synapse, and Databricks.
- Knowledge of Azure DevOps for CI/CD automation.
- Understanding of data governance, security, access controls, and lineage.
- Ability to support Power BI reporting and semantic models.
- Bachelor's degree in any discipline.