Summary
What you’ll impact
Our company is seeking a Senior Data Engineer to design and build scalable AI-ready data pipelines using Python, Snowflake, and dbt. The role focuses on modern AI architectures, ingestion frameworks, and performance optimization for production-grade solutions. The position offers strong technical influence and architecture ownership in a remote, U.S.-only setting.
Responsibilities
What you'll do
- Build & Scale: Architect and optimize scalable Python + Snowflake + dbt pipelines supporting both analytics and AI production use cases.
- AI Architecture: Design modern data architectures for LLM workflows, RAG patterns, semantic search, and AI-enabled applications.
- Ingestion Frameworks: Develop robust API and event-driven ingestion frameworks for structured and unstructured data.
- AI Readiness: Prepare high-quality, curated datasets optimized for AI/ML inference and downstream consumption.
- Performance & Costs: Fine-tune Snowflake performance, optimize transformation efficiency, and keep compute costs low.
- Reliability & Quality: Improve overall platform reliability, observability, and data quality standards.
- Collaboration & Leadership: Partner with engineering and business teams while establishing modern engineering standards and best practices.
Requirements
What you’ll bring
- 7+ years of hands-on Data Engineering experience.
- Core Tech Stack: Strong mastery of Python, Snowflake, SQL, and dbt.
- AI/LLM Experience: Hands-on experience supporting AI/LLM workflows (Open AI, Anthropic, embeddings, vector search, semantic retrieval, or RAG architectures).
- Orchestration: Hands-on experience with Airflow or similar orchestration engines.
- Production Focus: Proven track record of building scalable platforms and handling imperfect enterprise data at scale.
- Autonomy: Ability to lead architectural decisions and work independently in a fast-moving environment.
- Need U.S. Citizens