Azure Data Engineer
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What you'll do
- Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
- Build and maintain data integration workflows from various data sources to Snowflake.
- Write efficient and optimized SQL queries for data extraction and transformation.
- Work with stakeholders to understand business requirements and translate them into technical solutions.
- Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
- Maintain and enforce data quality, governance, and documentation standards.
- Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment.
What they're looking for
- Strong experience with Azure Cloud Platform services.
- Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines.
- Proficiency in SQL for data analysis and transformation.
- Hands-on experience with Snowflake and SnowSQL for data warehousing.
- Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse.
- Experience working in cloud-based data environments with large-scale datasets.
- Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or a related field.
- 8+ years of experience in data engineering roles using Azure and Snowflake.
Nice to have
- Experience with Azure Data Lake, Azure Synapse, or Azure Functions.
- Familiarity with Python or PySpark for custom data transformations.
- Understanding of CI/CD pipelines and DevOps for data workflows.
- Exposure to data governance, metadata management, or data catalog tools.
- Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Role: Azure Data Engineer
Location: Gurugram
Work Mode: Hybrid
Key Responsibilities:
• Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake,
and DBT.
• Build and maintain data integration workflows from various data sources to
Snowflake.
• Write efficient and optimized SQL queries for data extraction and transformation.
• Work with stakeholders to understand business requirements and translate them
into technical solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and
reliability.
• Maintain and enforce data quality, governance, and documentation standards.
• Collaborate with data analysts, architects, and DevOps teams in a cloud-native
environment.
Must-Have Skills:
• Strong experience with Azure Cloud Platform services.
• Proven expertise in Azure Data Factory (ADF) for orchestrating and automating
data pipelines.
• Proficiency in SQL for data analysis and transformation.
• Hands-on experience with Snowflake and SnowSQL for data warehousing.
• Practical knowledge of DBT (Data Build Tool) for transforming data in the
warehouse.
• Experience working in cloud-based data environments with large-scale datasets.
Good-to-Have Skills:
• Experience with Azure Data Lake, Azure Synapse, or Azure Functions.
• Familiarity with Python or PySpark for custom data transformations.
• Understanding of CI/CD pipelines and DevOps for data workflows.
• Exposure to data governance, metadata management, or data catalog tools.
• Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus.
Qualifications:
• Bachelor’s or master’s degree in computer science, Data Engineering,
Information Systems, or a related field.
• 8+ years of experience in data engineering roles using Azure and Snowflake.
Key Skills: Azure, Snowflake, SQL, Data Factory, DBT
Company
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