Snowflake Data Engineer - Python/SQL/ETL

About QualMinds :

We at QualMinds design & develop world-class digital products and custom software for Startups, Scale-ups & Enterprises with our world-class engineering team. We assemble a great team of frontend, backend, full-stack, QA automation, UI/UX, DevOps, data science, machine learning, and agile experts to help our clients propel their pursuit of digital excellence. Our engineering community at QualMinds is always passionate about building customer-centric software with the highest quality, performance, security, scalability, and lowest failure rates. We are looking for an experienced Snowflake Developer / Senior Data Engineer with strong expertise in building scalable data pipelines, optimizing Snowflake environments, and delivering high-quality data solutions. The ideal candidate will have 5-10 years of hands-on experience in data engineering with a deep understanding of Snowflake, SQL, and cloud-based ETL tools.

Key Responsibilities : 1. Snowflake Development & Architecture :

• Design and develop scalable Snowflake data models including fact, dimension, and staging layers.

• Define and implement clustering keys, partition strategies, and effective micro-partition usage for large tables.

• Optimize Snowflake storage and compute architecture based on business workloads.

2. Data Ingestion & Pipeline Development :

• Build and maintain ETL/ELT pipelines using : Snowflake SQL, Snowpipe, Azure Data Factory (ADF), Matillion

• Implement incremental / delta load mechanisms and ensure data freshness.

• Perform data validation, deduplication, and consistency checks across sources and targets.

3. SQL & Stored Procedure Development :

• Write complex SQL queries, views, and stored procedures using : Snowflake Scripting, JavaScript (for Snowflake stored procedures)

• Conduct SQL performance tuning and query optimization.

4. Performance Tuning & Optimization :

• Analyze and troubleshoot slow-running queries using Query Profile and Snowflake monitoring tools.

• Optimize performance through warehouse sizing, caching strategies, micro-partition pruning, and query structure improvements.

• Ensure efficient resource consumption and cost optimization.

5. Security, Governance & Access Control :

• Implement and maintain RBAC (Role-Based Access Control).

• Manage roles, users, privileges, and secure data sharing.

• Ensure compliance with organizational security standards and best practices.

6. Monitoring, Troubleshooting & Operations :

• Implement robust error handling including logging, retry mechanisms, and alerting.