Data Engineer – Snowflake
Summary
Designs and maintains Snowflake-based data pipelines, focusing on ETL/ELT workflows, Snowpark automation, and cloud-native data operations to enable scalable data processing and analytics.
- Strong hands-on experience designing and operating Snowflake in production
- Deep experience with Snowflake features, like Snowpark, Streams & Tasks, Snowpipe, Time Travel, cloning, materialized views, external functions and user-defined functions.
- Hands-on ETL/ELT development experience with dbt, SQL, and one or more ingestion tools (Streamsets, Fivetran, Matillion, Airbyte, Kafka connectors).
- Proficient in Python (Snowpark/connector), SQL tuning and query optimization techniques.
- Experience with IaC and automation (Terraform, GitHub Actions, Jenkins, or equivalent).
- Strong knowledge of cloud platforms and native services (AWS, Azure or GCP) as they relate to Snowflake deployment and integrations.
- Solid understanding of medallion architecture, data modeling patterns, data governance, and secure data sharing.
- Demonstrated ability to implement CI/CD, automated testing and production operational practices for data workloads.
Preferred qualifications
- Snowflake SnowPro Core or advanced Snowflake certifications.
- Experience with dbt (core or Cloud) for transformation and modular SQL engineering.
- Experience with data virtualization, data catalogs or data lineage tools.
- Familiarity with analytics and BI integrations (Looker, Tableau, Power BI) and building Snowflake-optimized semantic layers.
- Experience building internal developer tools or data apps using Snowpark or lightweight web frameworks.