Azure Lead Data Engineer

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 DataStage, Netezza, 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.

• Strong problem-solving, communication, and collaboration skills.