We are looking for a seasoned ETL Developer with over 6 years of dedicated experience in architecting, building, and maintaining advanced data integration and transformation solutions. This role demands robust, hands-on proficiency in Snowflake, Data Build Tool (DBT), and Fivetran, complemented by exceptional SQL development capabilities. The ideal candidate will be adept at constructing scalable data pipelines, implementing rigorous data quality controls, and actively supporting enterprise data warehousing and analytics objectives.

Furthermore, familiarity with CI/CD methodologies, Git-based development workflows, and deployment automation is essential for contributing to modern data engineering practices.

Key responsibilities include designing, developing, and maintaining scalable ETL/ELT pipelines for data ingestion, transformation, and loading from diverse sources. You will build and optimize data transformation pipelines using DBT, adhering to modular and reusable development principles. Developing and managing data models within Snowflake, encompassing staging, intermediate, and curated layers, is also crucial.

You will configure, manage, and troubleshoot data ingestion pipelines with Fivetran, and craft complex, high-performance SQL queries, stored procedures, views, and data validation scripts. Implementing data quality checks, reconciliation processes, and monitoring mechanisms to ensure data accuracy and reliability are core duties. Collaboration with Data Architects, Engineers, Analysts, and Business stakeholders to translate requirements into effective data solutions will be vital. Performance optimization of Snowflake through partitioning, clustering, warehouse sizing, and query tuning is expected.

Additional responsibilities involve developing and maintaining source-to-target mappings, technical specifications, and data lineage documentation. You will be responsible for troubleshooting production issues, performing root cause analysis for data-related incidents, and participating in code reviews to uphold development standards. Supporting automated deployment processes across all environments is also part of the role.

A minimum of 6 years in Data Engineering is required, with at least 2 years specifically focused on Fivetran, Snowflake, and DBT. Strong hands-on expertise in the Snowflake Data Cloud is essential.

Demonstrate substantial hands-on experience with DBT (Data Build Tool) for sophisticated data transformations and modeling. Experience in designing and developing data pipelines, particularly across Bronze and Silver layers within modern data lakehouse architectures, is expected. A solid understanding of data warehousing concepts, dimensional modeling, and various data transformation patterns is necessary.

Proficiency in SQL performance optimization and Snowflake tuning techniques is a key requirement. Familiarity with CI/CD practices, Git-based development, and deployment automation is also important. An understanding of data quality, testing, monitoring, and governance frameworks will contribute to success in this role.