About this role
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.
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.
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.