- 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.