W3Global
Snowflake Cortex Semantic & Agent Engineer
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Snowflake Cortex Semantic & Agent Engineer
Role Overview
We are seeking a hands-on Snowflake Cortex Semantic & Agent Engineer to build Snowflake Cortex Skills, agent capabilities, reusable skill packages and tools for governed Finance AI use cases. The engineer will implement Talk-to-Data experiences, connect agents to approved semantic models and business context, and improve response quality using business questions, verified queries, interaction patterns and identified response gaps.
Required Experience
- 8-12 years of experience in software engineering, AI engineering, data engineering, analytics engineering, semantic modelling or enterprise application development.
- Hands-on experience with Snowflake, SQL and the development of data-driven applications or analytical solutions.
- Mandatory hands-on experience with Snowflake Cortex semantic models, including business entities, relationships, dimensions, measures, metrics, verified queries and semantic grounding.
- Mandatory working knowledge of the COCO SDK, including its use for enterprise context, semantic assets or agent integration.
- Experience building AI-ready data foundations with governed, discoverable and context-rich data products for agentic and analytical use cases.
- Experience implementing model-based analytics using reusable semantic definitions, governed measures and calculation models.
- Hands-on experience integrating AI agents with semantic models, enterprise data, APIs, tools and services using secure and observable patterns.
- Experience developing in Python and integrating REST APIs, JSON-based services and enterprise systems.
- Experience testing AI or data solutions using repeatable datasets, expected results and automated quality checks.
- Strong troubleshooting, code-quality, documentation and Agile delivery skills.
- Prior experience in Finance, banking, capital markets, wealth management or regulated reporting is preferred.
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Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, Data Science or a related discipline.
- SnowPro Core or another relevant Snowflake certification is preferred.
- Experience with enterprise chat, business-intelligence or conversational analytics integrations is advantageous.
- Deep experience with semantic modelling, metadata platforms, governed data products and model-based analytics is strongly preferred.
- Experience delivering AI capabilities within a regulated enterprise environment is preferred.
Success Measures
- Cortex Skills and agents answer prioritised Finance questions using governed data and approved business context.
- Response accuracy and coverage improve through systematic analysis of verified queries, interaction patterns and response gaps.
- Reusable tools and skill packages reduce duplication and accelerate additional Finance AI use cases.
- Evaluation, regression and confidence controls provide clear evidence of agent quality and behavioural changes.
- Delivered capabilities meet agreed security, performance, reliability, documentation and production-readiness standards.
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Core Technical & Domain Skills
Capability
Snowflake Cortex
- Cortex Skills, Cortex Agents, verified queries, semantic grounding and Talk-to-Data
Agentic AI
- Agent workflows, tools, prompts, context management, orchestration and reusable skill packages
Development
- Python, advanced SQL, REST APIs, JSON, Git and CI/CD fundamentals
AI quality
- Golden datasets, evaluation, regression testing, confidence scoring, grounding and feedback loops
Cortex semantic modelling (Mandatory)
- Cortex semantic models, entities, relationships, dimensions, measures, metrics, verified queries and semantic grounding
Security & operations
- Entitlements, data protection, prompt-injection awareness, monitoring, logging and runbooks
Finance awareness
- GL, P&L, Revenue, Spend, financial measures or management reporting preferred
COCO SDK (Mandatory)
- Working knowledge of COCO SDK for enterprise context, semantic asset and agent integration
AI-ready data foundation
- Governed data products, metadata, lineage, quality, entitlements, discoverability and contextual enrichment
Model-based analytics
- Reusable semantic definitions, governed calculations, Finance measures and consistent analytical outcomes
Agent integration
- Secure integration with Cortex, semantic models, enterprise APIs, tools and services; orchestration and observability
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