Snowflake developer

About the Role We are seeking an experienced Snowflake Developer with deep expertise in Matillion (ETL / Matillion Data Productivity Cloud) to design, build, and optimize data integration pipelines feeding the Snowflake Data Cloud. This role is central to our data platform strategy — responsible for architecting reliable ELT/ETL workflows, ensuring data quality, and enabling analytics and reporting teams with clean, well-modeled, performant data in Snowflake. Key Responsibilities • Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines using Matillion (ETL for Snowflake or Matillion Data Productivity Cloud) to ingest data from multiple source systems into Snowflake. • Orchestration: Develop, orchestrate, and monitor Matillion jobs, orchestration flows, and transformation jobs, ensuring robust error handling, logging, and ing. • Data Modeling & SQL: Write and optimize complex SQL, stored procedures, and Snowflake-native transformations (Streams, Tasks, Dynamic Tables) to support pipeline logic. • Performance & Cost Optimization: Tune Snowflake warehouses, clustering, and query performance, and optimize Matillion job design for cost efficiency and speed. • Data Quality: Implement data validation, reconciliation, and quality checks across ingestion and transformation layers. • Security & Governance: Apply Snowflake and Matillion security best practices — role-based access control, secure credential/connection management, network policies, and data masking. • Integration: Connect Matillion pipelines to a variety of sources (databases, APIs, flat files, SaaS applications, cloud storage such as S3/Azure Blob/GCS) landing into Snowflake. • DevOps & Deployment: Build and manage CI/CD processes for Matillion pipeline deployment across dev/test/prod environments. • Collaboration: Partner with data architects, analysts, and business stakeholders to understand data requirements and translate them into efficient pipeline designs. • Documentation & Support: Maintain clear documentation of data flows, transformation logic, and pipeline architecture; troubleshoot and resolve production data issues. • Data Analysis: Analyze ingested and transformed data within Snowflake to validate accuracy, identify trends, and produce reports/dashboards that support business and analytics teams.