Lead Snowflake Engineer

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth.

About The Role 

We are looking for an experienced Lead Data Engineer with strong expertise in Python, Matillion, and Snowflake to design, develop, and optimize scalable data pipelines and cloud-based data warehouse solutions. The ideal candidate should have hands-on experience in ETL/ELT development, data modeling, and cloud data engineering while working in an agile environment.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Matillion.
• Build and optimize data warehouse solutions on Snowflake.
• Develop robust data processing frameworks and automation scripts using Python.
• Create and maintain data models, transformations, and workflows to support business analytics.
• Optimize Snowflake performance, including query tuning, clustering, and warehouse management.
• Integrate data from multiple structured and unstructured sources.
• Collaborate with business stakeholders, analysts, and cross-functional engineering teams to deliver high-quality data solutions.
• Implement data quality, validation, monitoring, and error-handling mechanisms.
• Participate in code reviews, testing, deployment, and production support activities.
• Follow best practices for security, governance, and documentation.

• 6+ years of experience in Data Engineering.
• Strong hands-on experience with Python, Matillion, and Snowflake.
• Experience building ETL/ELT pipelines and data integration solutions.
• Strong SQL skills with experience in query optimization.
• Good understanding of data warehousing concepts and dimensional data modeling.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Git, CI/CD pipelines, and Agile methodologies.
• Strong analytical, troubleshooting, and problem-solving

• Experience with orchestration tools such as Airflow.
• Exposure to DBT is an added advantage.
• Knowledge of REST APIs and data integration techniques.
• Familiarity with data governance and security best practices.