Sr Data Engineer (CE50SI RM 4572)

Position: Sr Data Engineer (CE50SI RM 4572)

Shift timing : 10am-7pm IST with flexibility to adjust for client calls/meetings/release schedules
Work Mode : Work from Office
Education Required : Bachelor’s degree in computer science or a related field

Prefer in-person if candidate is from same office location as that of the panel, wherever possible

Qualification:

• 4 years of bachelor’s degree in computer science or equivalent
• 5+ years of working experience in Data Platforms and Data Engineering

Tools: Azure Data Factory, Azure Databricks, Azure SQL Database, SQL, Python (PySpark), Microsoft Power BI

Mandatory Skills:

• 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.
• Should be able to work collaboratively with other team members, as well as users for operational support
• Expertise in Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, SQL Stored Procedure development, and performance tuning.
• Should possess very good communication with strong business and data analysis skills
• Experience in using Agile methodologies
• Experience in developing and working on Power BI reports for enterprise level reports.

Key Responsibilities:

• Develop, fine-tune, automate, and maintain ETL pipelines using Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, and SQL Server Stored Procedures.
• Develop ETL solutions using data integration tools for interfacing between source application and the Enterprise Data Warehouse
• Document ETL data mappings, data dictionaries, processes, programs, and solutions as per established standards for data governance
• Integrate ETL development with existing projects to maximize object reuse
• Create, execute, and document unit test plans for ETL and data integration processes and programs
• 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.
• Troubleshoot data issues and defects to determine root cause
• Performance tuning of the ETL process and SQL queries, and recommend and implement ETL and query tuning techniques
• Develop and create transformation queries, views, and stored procedures for ETL processes, and process automations

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