Senior Snowflake Engineer

3 days ago

Mumbai, India LearningMate Full time

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

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