We’re looking for a Snowflake Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions on Snowflake. You’ll partner with data, analytics, and product teams to deliver reliable, secure, and cost-efficient data products that power business decisions. Key Responsibilities Design and implement end-to-end ELT/ETL pipelines into Snowflake from diverse sources (batch and streaming). Model data for analytics use cases (dimensional and data vault) and build reusable data products and marts. Optimize Snowflake performance (warehouse sizing, query tuning, micro-partitioning, clustering, pruning). Implement data ingestion using Snowpipe, tasks, streams, and external stages (S3/ADLS/GCS). Ensure data quality, lineage, and observability (tests, alerts, SLAs, and documentation). Enforce security and governance (RBAC, masking, row-level access, data sharing, audit, compliance). Implement cost controls and monitoring (resource monitors, warehouse policies, storage lifecycle). Collaborate with analytics engineers, data scientists, and business stakeholders to translate requirements into scalable solutions. Automate deployments and environment management via CI/CD and infrastructure-as-code. Maintain standards, patterns, and best practices for Snowflake development. Required Qualifications data engineering (Snowflake-focused for mid-level; 6–8+ for senior). Strong SQL and data modeling skills (star/snowflake schemas, data vault, incremental patterns). Hands-on with core Snowflake capabilities: Virtual Warehouses, Databases/Schemas Stages, Snowpipe, Streams & Tasks Time Travel, Zero-Copy Cloning External tables and file formats