ETL Developer

Key Responsibilities Design, develop and maintain scalable data pipelines using Snowflake, Azure and dbt. Develop complex data transformation and business logic using dbt models and advanced SQL. Build and optimize Snowflake objects including databases, schemas, tables, views and other data-processing components. Develop data ingestion and integration solutions for loading data from multiple upstream systems into the Snowflake platform. Implement incremental processing, reusable transformation models and dependency-driven workflows using dbt. Develop automated data-quality checks, reconciliation and validation controls to ensure completeness and accuracy of reporting data. Optimize SQL queries and Snowflake workloads for performance, scalability and efficient resource utilization. Work with Azure-based data services and orchestration frameworks supporting ingestion, transformation and downstream delivery. Troubleshoot data-quality, pipeline and production-processing issues and perform root-cause analysis. Support development, testing, release and production implementation activities. Work closely with business analysts, application teams and downstream reporting teams to translate requirements into technical solutions. Maintain technical documentation covering data flows, transformations, dependencies and operational procedures. Follow appropriate Git-based version control, code review and CI/CD practices for dbt and data engineering components. Participate in production support and ensure timely resolution of batch and data-processing failures. Mandatory Technical Skills Snowflake Strong hands-on experience with Snowflake Data Cloud. Advanced Snowflake SQL and data transformation experience. Experience working with tables, views, stages, file formats and data-loading patterns. Good understanding of Snowflake performance optimization and warehouse/resource management. Experience troubleshooting large-volume data-processing workloads. Strong hands-on development experience with dbt. Experience developing reusable dbt models using: Sources Staging and transformation models, Incremental models ,Macros/Jinja Microsoft Azure Strong understanding of Azure-based data engineering architecture. Experience building or supporting automated ingestion and orchestration workflows. SQL & Data Engineering Strong SQL development and performance-tuning skills. Experience handling high-volume datasets and complex transformations. Strong understanding of: Data modeling Data-quality validation

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