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Senior Snowflake Engineer

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bangalore, 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