Job Description
Responsibilities:
- Design, develop, and optimize ETL/ELT pipelines using Azure Synapse, Databricks, and Microsoft Fabric
- Work with structured and semi-structured data across various storage systems including ADLS Gen2 and OneLake
- Implement and manage medallion architecture (Bronze, Silver, Gold) in Delta Lake or Lakehouse environments
- Collaborate with BI developers, data scientists, and business stakeholders to understand data requirements
- Tune Spark and SQL jobs for performance and cost efficiency
- Build dataflows, notebooks, pipelines in Fabric to support reporting, analytics, and archival workflows
- Maintain and monitor data quality, lineage, and governance using tools like Purview, Fabric Data Activator, etc.
- Automate data workflows and enforce data security and PII masking policies
- Participate in cloud migration and modernization initiatives related to data platforms
Required Skills and Qualifications:
- 6+ years of data engineering experience with strong hands-on work in
- Azure Synapse Analytics (Dedicated SQL Pools, Pipelines, Serverless SQL)
- Azure Databricks (PySpark, Delta Lake, notebooks, job orchestration)
- Microsoft Fabric (Lakehouse, Warehouse, Dataflows Gen2, Notebooks, Pipelines)
- Strong SQL and PySpark coding skills
- Experience with Data Lake architecture, partitioning, data modeling, and performance tuning
- Solid understanding of CI/CD for data pipelines using DevOps or Git
- Familiar with Power BI integration and use of Fabric workspaces
- Experience with Dataverse, D365, or exporting data from ERP/CRM systems is a plus
- Knowledge of data security, archival strategies, and data lifecycle management
Preferred Qualifications:
- Azure certifications (e.g., DP-203, AZ-305, Fabric certifications)
- Experience with Delta Live Tables, Fabric KQL, or Real-Time Analytics
- Familiarity with tools like ADF, Event Grid, Power Automate, or Logic Apps
- Exposure to big data monitoring and cost optimization strategies
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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