Senior Snowflake Engineer

Position : Snowflake Engineer

Full time - Hybrid / Remote work mode

Role overview

Own the design and delivery of data + GenAI solutions where Snowflake is the primary platform. Expect a practical split of ~60% data engineering / Snowflake optimization and ~40% GenAI / Cortex work (good to have).

What you’ll do

Build and productionize data pipelines in Snowflake (Snowflake SQL, Tasks / Streams, Snowpark / Python) with strong SLAs, cost controls, and monitoring

Use Snowflake Cortex (LLM functions, vector search, model inference) to ship RAG / analytics assistants, summarization, and workflow automation

Prototype quickly, then harden to production with CI / CD, logging, alerting, and access controls

Integrate external LLM services or vector stores when Snowflake-native features aren’t the best fit, keeping data gravity in Snowflake

Apply governance and security best practices (RBAC, masking, tags, row-level / column-level security)

Collaborate with data product owners and analysts to scope use cases, estimate effort, and measure impact

Document patterns and coach teammates on Snowflake / Cortex usage

Must-have qualifications

6–8 years in data engineering / analytics (or equivalent impact), including 1+ year building in Snowflake in production.

Strong SQL and Python ; hands-on with Snowpark and UDFs (Python preferred).

Practical experience with at least one Snowflake AI capability : Cortex LLM functions , vector search , or model inference (POCs are fine)

Proven ability to ship : from prototype → production with quality, cost, and performance in mind

Working knowledge of data security / governance and performance tuning in Snowflake

Nice to have

Snowflake certifications (SnowPro Core / Advanced / Data Engineering)

Experience with RAG architectures , embeddings, LangChain / LlamaIndex , or ML lifecycle tools (MLflow)

dbt, Git-based CI / CD, Docker; basic observability for data / LLM systems

Data viz (e.g., Power BI / Tableau) or building simple REST / Streamlit apps for demos.

Prior work with Azure OpenAI, GCP Vertex AI, Databricks, or other cloud AI stack