Snowflake Developer

Job Responsibilities -

• 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 arent 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

• 68 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.