Lead Data Engineer

Job Description: 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.

Responsibilities: 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.
• Provide technical leadership and mentorship to junior data engineers.
• 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: Qualifications:

• Bachelor’s degree in Data Engineering or a related field.
• 8+ years of experience in data engineering roles using Azure and Snowflake.
Strong problem-solving, communication, and collaboration skills.

The base salary for this role ranges from $110-140k per year, based on skills and experience.