Snowflake Engineer (Snowflake Cortex & Data Engineering)
Job Family:
Data Science & Analysis Travel Required:
Up to 10% Clearance Required:
Ability to Obtain Public Trust What You Will Do:
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Design, develop, and optimize Snowflake data solutions supporting enterprise analytics, reporting, and data-driven decision making.
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Build scalable batch and near real-time data ingestion and processing pipelines using Snowpipe, Streams, Tasks, Dynamic Tables, and Snowpark.
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Develop and maintain advanced SQL-based solutions, including complex stored procedures, UDFs, views, and reusable data transformation frameworks.
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Design and implement enterprise-grade ELT/ETL pipelines and metadata-driven automation frameworks.
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Optimize Snowflake performance, scalability, reliability, and cost through query tuning, workload optimization, and platform best practices.
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Implement secure, governed data solutions leveraging Snowflake native capabilities, including RBAC, data sharing, and governance controls.
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Design and support enterprise data warehouse, data mart, and lakehouse architectures.
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Integrate data from cloud, on-premises, API, and SaaS data sources.
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Collaborate with architects, analysts, product owners, and business stakeholders to deliver high-quality data products and solutions.
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Provide production support, monitoring, troubleshooting, incident resolution, and continuous platform improvement.
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Support AI and advanced analytics initiatives leveraging Snowflake Cortex, Snowpark, and related Snowflake capabilities.
What You Will Need:
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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 Degree
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FIVE (5) or more years of data engineering experience, including TWO (2) years of hands-on Snowflake experience.
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Experience in SQL development with extensive experience building and optimizing complex queries against large datasets.
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Experience developing and maintaining stored procedures, UDFs, views, and data transformation logic.
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Deep understanding of Snowflake architecture, including Virtual Warehouses, micro-partitions, clustering, caching, and performance optimization.
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Hands-on experience designing, implementing, and supporting Snowflake-native capabilities, including Snowpipe, Streams, Tasks, Dynamic Tables, Change Data Capture (CDC) patterns
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Experience administering secure, scalable Snowflake environments and implementing RBAC, data access controls, and governance frameworks.
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Experience building scalable ELT/ETL frameworks and enterprise data pipelines.
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Experience with data quality, reconciliation, monitoring, and operational support processes.
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Knowledge of cloud platforms such as AWS, Azure, or GCP.
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Experience with CI/CD pipelines, Git-based source control, Infrastructure as Code (IaC), and automated deployment practices.
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Familiarity with production support, observability, incident management, and operational readiness best practices.
What Would Be Nice To Have:
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Hands-on experience implementing Snowflake Cortex capabilities and AI-powered data solutions.
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Familiarity with production support, observability, incident management, and operational readiness best practices.
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Experience with Cortex AI functions, semantic search, intelligent data applications, and AI-driven analytics.
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Experience leveraging Snowpark (Python) for advanced data engineering, analytics, and AI/ML workloads.
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Understanding of Retrieval-Augmented Generation (RAG), vector search, LLM-powered applications, and generative AI use cases within Snowflake.
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Experience with dbt and modern analytics engineering practices.
- Strong Python development experience.
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SnowPro Core, SnowPro Advanced, or other Snowflake certifications.
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Experience supporting regulated industries or large enterprise environments.
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Experience designing cloud