Senior Data Engineer (AI & Cloud Platforms)

Title: Senior Data Engineer (AI & Cloud Platforms)

Location: Remote

Need U.S. Citizens

If you would like to know a bit more about this opportunity, or are considering applying, then please read the following job information.

About the Role

Rockwoods is hiring a Senior Data Engineer for a high-visibility engagement with an insurance client.

This is not a traditional ETL or reporting role. We are looking for a senior engineer who understands how scalable data systems power modern AI applications including LLM integrations, semantic search, vector-based retrieval, AI-ready data modeling, and production-grade pipelines.

This role is for you if you:

• Enjoy solving messy, complex, real-world data problems.
• Build and optimize scalable systems hands-on.
• Understand performance, scale, and reliability inside out.
• Have moved beyond proof-of-concepts and deployed production-grade solutions.

If you want strong technical influence, architecture ownership, and the opportunity to build modern AI-ready data infrastructure, we'd love to connect.

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.

What We're Looking For

• 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.

Nice-to-Haves

• 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. xhyhwjd
• Experience designing reusable enterprise data frameworks.