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. - Solid 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. - Solid 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. - Valuable understanding of data quality, validation, and reconciliation techniques. - Strong problem-solving and analytical skills.

📌 Snowflake Data Engineer (Hyderabad)
🏢 Anblicks
📍 Hyderabad