Senior Data Engineer

Hybrid in Austin, TX, US • Posted 17 hours ago • Updated 17 hours ago
Contract Corp To Corp
Contract Independent
Contract W2
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Snowflake
  • SQL
  • ETL

Summary

Role Overview
As the Senior Data Engineer, you will be the technical visionary and hands-on architect for our enterprise AI initiatives. You will leverage the full Snowflake AI Data Cloud stack to design, build, and scale production-grade Generative AI applications, RAG (Retrieval-Augmented Generation) frameworks, and agentic workflows. You will bridge the gap between complex data engineering and advanced LLM implementation, ensuring our AI solutions are secure, governed, and high-performing.
Key Responsibilities
AI Architecture & Strategy: Lead the design of end-to-end AI solutions using Snowflake Cortex AI, including the implementation of LLM functions (AI_COMPLETE, AI_SUMMARIZE, etc.) and Cortex Search.
RAG & Document Intelligence: Build and optimize RAG pipelines that ground LLMs in enterprise data. Implement Document AI for extracting value from unstructured data (PDFs, images, etc.).
Advanced Data Engineering: Design scalable ELT/ETL pipelines using Snowpark (Python) and dbt. Oversee the creation of vector embeddings and the management of Vector Data Types within Snowflake.
Agentic Workflows: Develop "Agentic" AI systems that can reason through complex tasks and interact with enterprise datasets via natural language.
Governance & Security: Enforce Snowflake Horizon standards, ensuring all AI models and data products comply with RBAC, data masking, and differential privacy policies.
Mentorship & Leadership: Lead a squad of 3 5 engineers. Conduct code reviews, define best practices for AI/MLOps, and drive the technical roadmap in collaboration with stakeholders.
Technical Requirements
Category
Must-Have Skills
Snowflake Core
SnowPro Core/Advanced, Snowpark, Streams & Tasks, Dynamic Tables.
AI/ML Stack
Snowflake Cortex, Vector Search, ML Functions (Forecasting, Anomaly Detection).
Languages
Expert-level SQL and Python (specifically pandas, scikit-learn, and Snowpark).
AI Concepts
RAG architecture, Prompt Engineering, LLM Evaluation (metrics like faithfulness/relevancy).
Orchestration
Experience with Airflow or Snowflake-native orchestration; CI/CD via GitHub Actions/Terraform.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90932951
  • Position Id: 8925344
  • Posted 17 hours ago
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