Azure Data Engineer
At a glance
Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Create ETL and ELT workflows with Azure Data Factory, Snowflake and DBT
- Bring data from multiple sources into Snowflake, using SQL to extract and reshape it
- Translate stakeholder needs into technical plans, then diagnose pipeline issues and improve reliability
- Set data quality, governance and documentation practices while coordinating with analysts, architects and DevOps teams
What you bring
- At least four years working as a data engineer with Azure and Snowflake
- Strong Azure knowledge, including using Data Factory to schedule and automate pipelines
- You can use SQL, SnowSQL and DBT for data analysis, warehousing and transformations
- A bachelor's or master's degree in computer science, data engineering, information systems or a related discipline
Who this fits
This mid-level role suits a data engineer with experience building Azure pipelines and working with Snowflake. The position is hybrid in Gurugram, India.
From the 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.
• 4+ years of experience in data engineering roles using Azure and Snowflake.
Key Skills: Azure, Snowflake, SQL, Data Factory, DBT
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.
Bachelor’s or master’s degree in computer science, Data Engineering,
Information Systems, or a related field.
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