Snowflake Data Engineer

Mandatory Skills:
Snowflake Cortex, DBT , SQL

This role will support Agentic AI Engineering initiatives by designing and implementing Snowflake-based semantic data assets that enable trusted analytics, natural-language querying, and AI-assisted insights. Day to day, the engineer will build and optimize medallion-architecture data models across bronze, silver, and gold layers; develop semantic views and business-friendly abstractions on curated Snowflake data; partner with product, analytics, and engineering teams to translate requirements into reusable data products; and help operationalize Snowflake Cortex capabilities for semantic intelligence and agent-driven analytics use cases. The resource will also help establish engineering patterns for semantic layer implementation, data quality validation, performance tuning, lineage-aware transformations, and governed access patterns so that agentic and analytical workloads can scale reliably on Snowflake.

Responsibilities: -

Healthcare or payer domain experience, especially with member, claims, provider, quality, or reference data.

• Snowflake SQL: Highly skilled. Must be able to develop complex transformations, optimize performance, and work confidently with CTEs, advanced joins, and analytic/window functions.
• Snowflake Data Engineering: Strong real-world experience building curated data layers using medallion architecture principles across bronze, silver, and gold datasets.
• Semantic Modeling / Semantic Layer Engineering: Must be able to define business-friendly metrics, dimensions, grain, relationships, and reusable semantic views on top of Snowflake data.
• Snowflake Cortex / AI-Enabled Analytics: Experience supporting Snowflake Cortex-based analytics workflows, semantic intelligence, or agentic analytics use cases is strongly preferred.
• Data Quality, Profiling, and Validation: Must be able to identify natural and surrogate keys, assess cardinality and distribution, validate transformations, and ensure trustworthy semantic outputs.
• Strong communication and ownership: Able to work across engineering, product, and analytics partners, clarify requirements, and proactively drive work with limited direction.

Experience: 10+ Years

Location: Remote

Educational Qualifications: -

• Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.
• Technical certification in multiple technologies is desirable.

Skills: - Snowflake Cortex, DBT , SQL

Experience in evaluating / troubleshooting and measuring agent performance, identifying issues, and optimizing it
Experience with dbt, semantic view design, or governed self-service analytics patterns.
Python experience for automation, metadata processing, data validation, or AI-assisted engineering workflows.
·Exposure to agentic AI, natural language analytics, or Snowflake Cortex Analyst / Cortex Search use cases.

Specific technologies to be used and level of proficiency?
· Snowflake SQL: Highly skilled to expert level.
· Snowflake: Strong hands-on experience with performance tuning, secure data design, and curated data modeling.
· Semantic Modeling / Semantic Views: Strong proficiency in defining business metrics, dimensions, relationships, grain, and reusable semantic abstractions.
· Python: Some experience desired, with preference for intermediate or higher skill for automation and validation use cases.
· dbt: Preferred real-world experience developing modular transformations, tests, and deployment patterns.
· Snowflake Cortex: Preferred experience with Cortex-enabled analytics, semantic intelligence, or agent-supporting workflows.

Day to Day Activities:
• Design and implement scalable Snowflake data models and pipelines that align with business objectives and agentic AI use cases.
• Build curated bronze, silver, and gold data layers and reusable semantic assets that support trusted analytics and natural-language data access.
• Collaborate with product, analytics, and engineering partners to translate complex requirements into governed data products and semantic models.
• Optimize Snowflake queries, warehouse configurations, and transformation performance for reliability, scalability, and cost efficiency.
• Design and implement data quality validation, profiling, and testing strategies to improve trust in downstream semantic outputs.
• Contribute to lineage-aware transformation patterns, documentation, and engineering standards for reusable data assets.
• Use dbt where applicable to develop modular transformations, tests, and deployment patterns; prior hands-on dbt experience is preferred.
• Support Snowflake Cortex-enabled analytics, semantic intelligence, and agent-assisting workflows where applicable.
• Troubleshoot production issues and implement durable long-term solutions.
• Document architectural decisions, semantic definitions, and data lineage.