Alvys - Senior Data & AI Engineer
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Requirements
• Data Platform: Snowflake (Warehouse, Cortex AI/ML, Semantic Models, LLM Agents) • Data Platform: • Data Pipelines: dbt, Fivetran, Reverse ETL (Census) • Data Pipelines: • AI/ML: Snowflake Cortex, OpenAI, Azure Cognitive • AI/ML: • Backend/Infra: .NET/C#, Python, Azure Ecosystem, GitHub Actions • Backend/Infra: • 7+ years of experience in Data Engineering with a proven track record of delivering mission-critical data platforms. • Deep proficiency in Snowflake (Data Modeling, Query Optimization, Security, and Cortex AI functions). • Cortex AI • Expert-level skill in SQL and Python. Extensive experience with dbt and modern orchestration (Airflow/Dagster). • Python • Demonstrated experience building pipelines for ML or LLM-based applications, including feature engineering and model deployment. • ML or LLM-based applications • Competency in Azure (preferred) or other major cloud providers, including CI/CD and infrastructure-as-code principles. • Azure • Experience driving cross-team consensus on architectural decisions and mentoring junior/mid-level engineers. • The Way You Work • Ownership: You take end-to-end responsibility. If it’s in production, it’s yours—from the initial schema design to the final dashboard latency. • Ownership: • Pragmatism: You believe technical debt is a strategic choice. You choose solutions that scale and solve real problems over theoretical "perfection." • Pragmatism: • Simplicity: You prioritize modularity and clean design to reduce cognitive load in a complex logistics domain. • Simplicity: • Transparency: You democratize data. You ensure insights are accessible across the organization and participate in constructive feedback loops. • Transparency: • Equal Employment Opportunity
Responsibilities
• Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications. • LLM-based data products • Own the design and evolution of our Snowflake architecture. Lead the implementation of Snowflake Cortex for AI/ML workloads, including semantic models and LLM agents. • Snowflake Cortex • Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale. • ELT/Reverse ETL • Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter. • large-scale ML and LLM model development • Think holistically about the data estate. Reduce complexity through modularity and well-defined service boundaries (e.g., Medallion Architecture). • Serve as the go-to expert for emerging data trends. Mentor engineers and partner with Product and Design to translate complex business logic into automated deliverables.
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