Data Engineer, Snowflake (Mid-Level)

Full Tilt Data, LLC is a trusted data, analytics, and IT consulting firm specializing is health related services for the federal government. Established in 2023 by a group of founders that bring 15+ years of industry experience. We are passionate about harnessing the power of data through our comprehensive data management solutions. We mobilize the right people, skills, and technologies to help all types of organizations and companies improve their performance and data management.

Position Summary

We are looking for a Data Engineer, Snowflake (Mid-Level) to help deliver modern, secure data solutions for a high-impact federal program. In this role, you will support the development of scalable cloud data warehouse capabilities, data pipelines, access-control frameworks, applications, and APIs that enable federal agencies to integrate, analyze, and share mission-critical data. Candidates must be able to pass a background check equivalent to a Federal Public Trust clearance. This is a remote position, with a requirement to come into the office quarterly for in-person meetings.

Key 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.

Snowflake Focus Areas for This Role

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)

• Secure Data Sharing, text extraction/OCR, and Streamlit in Snowflake (secondary priority areas)

Required Qualifications

•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.

Preferred Qualifications

• 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.

The salary range provided represents the estimated compensation for new hires in this position, applicable across all locations. Actual offers may vary based on factors such as the candidate's skills, qualifications, experience, and market conditions. Full Tilt Data complements its base salary offering with a competitive package that includes health benefits, discretionary bonuses, and reimbursement for professional development and training.