Data Engineer with Azure- Senior Engineer (Level 1)
The role involves designing and implementing ETL pipelines on Azure using Data Factory, Databricks, and PySpark to support large‑scale data warehouses. The candidate must also collaborate with stakeholders, tune SQL performance, and create Power BI visualizations while following Agile practices.
Skills required
About this role
JD For Data Engineer
Experience: 5 Years
Tools: Azure Data Factory, Azure Databricks, Azure SQL Database, SQL, Python (PySpark), Microsoft Power BI
Mandatory Skills:
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Should be well-versed in the design and development of ETL solutions using Azure Data Factory, Azure Databricks, Python (PySpark), and SQL for large-scale data warehouses.
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Should be able to work collaboratively with other team members, as well as users for operational support
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Expertise in Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, SQL Stored Procedure development, and performance tuning.
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Should possess very good communication with strong business and data analysis skills
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Experience in using Agile methodologies
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Experience in developing and working on Power BI reports for enterprise level reports.
Key Responsibilities:
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Develop, fine-tune, automate, and maintain ETL pipelines using Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, and SQL Server Stored Procedures.
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Develop ETL solutions using data integration tools for interfacing between source application and the Enterprise Data Warehouse
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Document ETL data mappings, data dictionaries, processes, programs, and solutions as per established standards for data governance
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Integrate ETL development with existing projects to maximize object reuse
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Create, execute, and document unit test plans for ETL and data integration processes and programs
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Work with the peers in data team to assess and troubleshoot potential data quality issues at key intake points such as validating control totals at intake.
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Troubleshoot data issues and defects to determine root cause
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Performance tuning of the ETL process and SQL queries, and recommend and implement ETL and query tuning techniques
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Develop and create transformation queries, views, and stored procedures for ETL processes, and process automations
