Snowflake Data Engineer

We are looking for an experienced Snowflake Data Engineer with 7+ years of experience in data engineering, data warehousing, and ETL/ELT development. The ideal candidate should have strong hands-on expertise in Snowflake, Python/PySpark, SQL, and DBT and be capable of designing, developing, and optimizing scalable data pipelines and data warehouse solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Snowflake, Python/PySpark, SQL, and DBT.
• Develop and optimize complex SQL queries, stored procedures, views, and data transformation logic.
• Build robust ETL/ELT pipelines for ingesting and transforming data from multiple sources into Snowflake.
• Develop data transformation models using DBT (Data Build Tool), including staging, intermediate, and analytical models.
• Implement data quality checks, validation, reconciliation, and monitoring processes.
• Optimize Snowflake queries, warehouse utilization, storage, and overall data-processing performance.
• Develop PySpark/Python scripts for large-scale data processing and transformation.
• Work with structured and semi-structured data such as JSON, XML, and CSV within Snowflake.
• Implement incremental data loads and efficiently handle large data volumes.
• Follow best practices for data modeling, including fact/dimension tables, star schema, and dimensional modeling.
• Collaborate with data architects, analysts, developers, and business stakeholders to understand data requirements.
• Troubleshoot data pipeline failures, performance issues, and data inconsistencies.
• Participate in code reviews and ensure development follows engineering and data governance standards.
• Maintain technical documentation related to data pipelines, transformations, and data models.

Required Skills

• 7+ years of experience in Data Engineering or a similar role.
• Strong hands-on experience with Snowflake.
• Strong proficiency in SQL, including complex queries, CTEs, window functions, joins, and query optimization.
• Strong programming experience in Python and/or PySpark.
• Hands-on experience with DBT (Data Build Tool) and DBT-based data transformation.
• Strong understanding of ETL/ELT concepts and data pipeline architecture.
• Experience with data warehouse concepts and dimensional data modeling.
• Experience working with large datasets and optimizing data processing workloads.
• Good understanding of data quality, validation, and reconciliation techniques.
• Strong problem-solving and analytical skills.