Senior Snowflake Engineer (Snowflake Cortex & Data Engineering

Design, develop, and optimize Snowflake data solutions supporting enterprise analytics, reporting, and data-driven decision making.

Build scalable batch and near real-time data ingestion and processing pipelines using Snowpipe, Streams, Tasks, Dynamic Tables, and Snowpark.

Develop and maintain advanced SQL-based solutions, including complex stored procedures, UDFs, views, and reusable data transformation frameworks.

Design and implement enterprise-grade ELT/ETL pipelines and metadata-driven automation frameworks.

Optimize Snowflake performance, scalability, reliability, and cost through query tuning, workload optimization, and platform best practices.

Implement secure, governed data solutions leveraging Snowflake native capabilities, including RBAC, data sharing, and governance controls.

Design and support enterprise data warehouse, data mart, and lakehouse architectures.

Integrate data from cloud, on-premises, API, and SaaS data sources.

Collaborate with architects, analysts, product owners, and business stakeholders to deliver high-quality data products and solutions.

Provide production support, monitoring, troubleshooting, incident resolution, and continuous platform improvement.

Support AI and advanced analytics initiatives leveraging Snowflake Cortex, Snowpark, and related Snowflake capabilities.

What You Will Do

• Design, develop, and optimize Snowflake data solutions supporting enterprise analytics, reporting, and data-driven decision making.
• Build scalable batch and near real-time data ingestion and processing pipelines using Snowpipe, Streams, Tasks, Dynamic Tables, and Snowpark.
• Develop and maintain advanced SQL-based solutions, including complex stored procedures, UDFs, views, and reusable data transformation frameworks.
• Design and implement enterprise-grade ELT/ETL pipelines and metadata-driven automation frameworks.
• Optimize Snowflake performance, scalability, reliability, and cost through query tuning, workload optimization, and platform best practices.
• Implement secure, governed data solutions leveraging Snowflake native capabilities, including RBAC, data sharing, and governance controls.
• Design and support enterprise data warehouse, data mart, and lakehouse architectures.
• Integrate data from cloud, on-premises, API, and SaaS data sources.
• Collaborate with architects, analysts, product owners, and business stakeholders to deliver high-quality data products and solutions.
• Provide production support, monitoring, troubleshooting, incident resolution, and continuous platform improvement.
• Support AI and advanced analytics initiatives leveraging Snowflake Cortex, Snowpark, and related Snowflake capabilities.

What You Will Need

• Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.
• Bachelors
• TEN (10) or more years of data engineering experience, including 2+ years of hands-on Snowflake experience.
• Experience in SQL development with extensive experience building and optimizing complex queries against large datasets.
• Experience developing and maintaining stored procedures, UDFs, views, and data transformation logic.
• Deep understanding of Snowflake architecture, including Virtual Warehouses, micro-partitions, clustering, caching, and performance optimization.
• Experience designing, implementing, and supporting Snowflake-native capabilities, including Snowpipe, Streams, Tasks, Dynamic Tables and Change Data Capture (CDC) patterns
• Experience administering secure, scalable Snowflake environments and implementing RBAC, data access controls, and governance frameworks.
• Experience building scalable ELT/ETL frameworks and enterprise data pipelines.
• Experience with data quality, reconciliation, monitoring, and operational support processes.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with CI/CD pipelines, Git-based source control, Infrastructure as Code (IaC), and automated deployment practices.
• Familiarity with production support, observability, incident management, and operational readiness best practices.

What Would Be…