Data Engineer, Snowflake (Mid-Level)

Summary

Full Tilt Data, LLC is a data, analytics, and IT consulting firm specializing in health-related services for the federal government. The company is seeking a mid-level Data Engineer to develop and maintain secure, scalable Snowflake data solutions, including pipelines, unified data models, RAG and vector search capabilities, CI/CD workflows, and policy enforcement integrations. The role also supports secure data sharing, OCR workflows, Streamlit applications, reusable reference implementations, and project reporting.

Responsibilities

• Design, build, and maintain data pipelines in Snowflake using SQL and Snowpark (Python), including schema normalization, metadata capture, data quality checks, and lineage tracking
• Develop and improve canonical/unified data model (UDM) structures, including star schema, fact, and dimension table design, to support repeatable onboarding of new agency datasets
• Build and integrate Retrieval-Augmented Generation (RAG) and vector search capabilities using Snowflake Cortex Search and Snowflake's native VECTOR data type to support AI-assisted contract search and natural language querying
• Contribute to Snowflake CI/CD pipelines (e.g., schemachange, dbt, or the Snowflake CLI/Snowflake DevOps framework) to improve deployment consistency, testing, and release velocity
• Develop Python-based integration layers connecting the OPA/Rego policy engine to Snowflake via Snowpark, enabling dynamic enforcement of row access policies and column-level masking at query time
• Support Secure Data Sharing configurations, text extraction/OCR workflows, and Streamlit-in-Snowflake applications as the team expands into these areas
• Package, document, and harden pipeline and data model patterns into reusable, well-documented reference implementations that other agencies and teams can adopt independently
• Participate in weekly standups and contribute to monthly status reporting on task progress and milestones

Skills

• 3–5+ years of hands-on data engineering experience, including at least 1–2 years working directly in Snowflake
• Strong proficiency in SQL and Snowpark (Python) for building and troubleshooting data pipelines
• Working knowledge of dimensional data modeling concepts (star schema, fact/dimension tables) and willingness to grow this into a core strength
• Experience with SQL and working across structured and semi-structured data sources (e.g., Snowflake VARIANT, JSON, Parquet)
• Familiarity with CI/CD concepts and version-controlled deployment workflows (Git-based)
• Comfortable working in a fast-paced, collaborative team environment and picking up new tools quickly
• Ability to obtain/maintain a Federal Public Trust clearance
• Candidates Should Have Direct, Hands-on Experience In One Or More Of The Following, And Be Comfortable Ramping Quickly Across The Rest
• Complex pipeline development and improvement on Snowflake using SQL and Snowpark
• Star schema and unified data model (UDM) design and refactoring
• RAG / vector search implementation (Snowflake Cortex Search) for search and natural language querying use cases
• Fact and dimension table design for analytic workloads
• Snowflake CI/CD and deployment best practices (schemachange, dbt, or Snowflake CLI/DevOps)
• Exposure to schemachange, dbt, or the Snowflake CLI/DevOps framework for infrastructure-as-code deployment tooling
• Exposure to vector search, embeddings, or RAG-style architectures — specifically Snowflake Cortex Search/vector data types, pgvector, FAISS, or Chroma, and embedding or generation model integration (e.g., Snowflake Cortex functions, Azure OpenAI, Bedrock)
• Familiarity with Open Policy Agent (OPA) / Rego or other policy-as-code frameworks
• Experience with a general-purpose backend language and a modern frontend framework (e.g., Go, Svelte, or similar), or with Streamlit, for adjacent API or UI work
• Prior experience on a federal contract or in a regulated data environment
• SnowPro certification(s) (SnowPro Core, or SnowPro Advanced: Data Engineer)
• Familiarity with Snowflake governance features (role-based access control, row access policies, column-level masking, object tagging, Access History/data lineage)
• Familiarity with federal compliance frameworks (e.g., NIST 800-53, FISMA, ATO processes) or experience handling CUI/PII
• An active Public Trust (or higher) clearance or investigation already in process
• Experience with data quality/testing frameworks

Qualifications

Must Haves

• 3–5+ years of hands-on data engineering experience, including at least 1–2 years working directly in Snowflake
• Strong proficiency in SQL and Snowpark (Python) for building and troubleshooting data pipelines
• Working knowledge of dimensional data modeling concepts (star schema, fact/dimension tables) and willingness to grow this into a core strength
• Experience with SQL and working across structured and semi-structured data sources (e.g., Snowflake VARIANT, JSON, Parquet)
• Familiarity with CI/CD concepts and version-controlled deployment workflows (Git-based)
• Comfortable working in a fast-paced, collaborative team environment and picking up new tools quickly
• Ability to obtain/maintain a Federal Public Trust clearance
• Candidates Should Have Direct, Hands-on Experience In One Or More Of The Following, And Be Comfortable Ramping Quickly Across The Rest
• Complex pipeline development and improvement on Snowflake using SQL and Snowpark
• Star schema and unified data model (UDM) design and refactoring
• RAG / vector search implementation (Snowflake Cortex Search) for search and natural language querying use cases
• Fact and dimension table design for analytic workloads
• Snowflake CI/CD and deployment best practices (schemachange, dbt, or Snowflake CLI/DevOps)
• Exposure to schemachange, dbt, or the Snowflake CLI/DevOps framework for infrastructure-as-code deployment tooling
• Exposure to vector search, embeddings, or RAG-style architectures — specifically Snowflake Cortex Search/vector data types, pgvector, FAISS, or Chroma, and embedding or generation model integration (e.g., Snowflake Cortex functions, Azure OpenAI, Bedrock)
• Familiarity with Open Policy Agent (OPA) / Rego or other policy-as-code frameworks
• Experience with a general-purpose backend language and a modern frontend framework (e.g., Go, Svelte, or similar), or with Streamlit, for adjacent API or UI work
• Prior experience on a federal contract or in a regulated data environment
• SnowPro certification(s) (SnowPro Core, or SnowPro Advanced: Data Engineer)
• Familiarity with Snowflake governance features (role-based access control, row access policies, column-level masking, object tagging, Access History/data lineage)
• Familiarity with federal compliance frameworks (e.g., NIST 800-53, FISMA, ATO processes) or experience handling CUI/PII
• An active Public Trust (or higher) clearance or investigation already in process
• Experience with data quality/testing frameworks

Benefits

• Health benefits
• Discretionary bonuses
• Reimbursement for professional development and training
• Remote position, with a requirement to come into the office quarterly for in-person meetings