Note: The job is a remote job and is open to candidates in USA. Rockwoods Inc is hiring a Senior Data Engineer for a high-visibility engagement with an insurance client. The role focuses on architecting scalable Python, Snowflake, and dbt data pipelines and modern data architectures that support LLM workflows, RAG, semantic search, vector retrieval, and AI-enabled applications. Responsibilities also include developing ingestion frameworks, preparing AI-ready datasets, optimizing performance and costs, improving reliability and data quality, and establishing engineering standards.
Responsibilities
- 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
Skills
- Need U.S. Citizens
- • 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
- • Insurance domain expertise (Claims, Policy, Billing, Underwriting, etc.)
- • Experience with specialized vector databases or AI search platforms
- • Exposure to MLOps or end-to-end AI deployment workflows
- • Experience designing reusable enterprise data frameworks
Company Overview