Back
Mid-level data role, common title and 5-year requirement create moderate applicant density.
Core data engineering skills (ETL, PySpark, ADF) are highly transferable across industries.
Many mandatory Azure, Databricks, PySpark, and 5-year experience requirements increase shortlisting rigidity.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, automate, and maintain ETL pipelines using Azure Data Factory, Azure Databricks, Python (PySpark), and SQL Server stored procedures for large-scale data warehouses.
Design and implement ETL solutions ensuring integration with enterprise data warehouses and adherence to data governance standards.
Perform troubleshooting and performance tuning of ETL processes and SQL queries; collaborate with teams for operational support and data quality assurance.
5 years of experience as a Data Engineer or similar role.
Proficiency in Azure Data Factory, Azure Databricks, Python (PySpark), Azure SQL Database, SQL, and SQL Stored Procedure development.
Familiarity with Agile methodologies and enterprise-level Power BI report development.
Location requirement: Ahmedabad, Gujarat, India.
Experienced in designing scalable ETL architectures and optimizations within Azure cloud environments.
Able to produce technical documentation aligned with data governance protocols and collaborate cross-functionally.
Skilled at diagnosing data quality issues and applying performance tuning for large data integration solutions in an enterprise setting.
