Forward Deployed Engineer
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Requirements
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. • 5+ years of professional experience in Data Engineering or a related role, with a strong focus on designing and implementing data architecture. • 5+ years • Strong proficiency with Snowflake (data modeling, performance optimization, SQL, security). • Strong proficiency with Snowflake • Proven track record building, scaling, and maintaining data pipelines and ETL/ELT processes in a production environment. • data pipelines • ETL/ELT • Experience with ML/LLM model development and deployment in production environments. • ML/LLM model development and deployment • Proficiency with SQL and one or more programming languages (Python, C#, TypeScript/Node). • Python, C#, TypeScript/Node • Experience with cloud-based data platforms (Azure, AWS, or GCP). • cloud-based • Experience working with real-time streaming solutions and Reverse ETL workflows. • real-time streaming • Familiarity with machine learning pipelines, LLM-based applications, feature engineering, and model deployment. • machine learning pipelines • LLM-based applications • Experience building large-scale, multi-tenant data platforms on Snowflake. • Snowflake • Experience with dbt or similar data transformation frameworks. • Strong understanding of dimensional modeling and data warehouse design patterns (Kimball, Inmon, Data Vault, or Medallion architecture). • Medallion architecture • Experience with Snowflake Cortex AI/ML for building LLM agents, semantic models, and AI-powered data products. • Snowflake Cortex AI/ML • Experience with LLM model fine-tuning, prompt engineering, and LLM-based data products. • LLM model fine-tuning, prompt engineering, and LLM-based data products • Experience with frontend development (React, Angular, or Vue) for building data applications and internal tools. • frontend development • Knowledge of MLOps best practices and ML orchestration tools (Airflow, Dagster, Prefect). • MLOps • Experience building data products, operational analytics, or embedded analytics. • Experience leading or mentoring other data engineers or analytics engineers. • Strong grasp of data governance, including compliance and security requirements. • data governance • Background in logistics or transportation systems is a bonus. • logistics or transportation • Equal Employment Opportunity
Responsibilities
• LLM-Based Data Strategy: Define and refine Alvys' strategy for LLM-based data products, including data preparation, feature engineering, and semantic layer design for AI applications. • LLM-Based Data Strategy • LLM-based data products • ML/LLM Development & Deployment: Build and operationalize large-scale ML and LLM model development and deployment pipelines using Snowflake Cortex and modern MLOps practices. • ML/LLM Development & Deployment • large-scale ML and LLM model development and deployment pipelines • Snowflake Architecture & Strategy: Lead the design and evolution of our Snowflake-centric data platform, including storage, processing, semantic modeling, and integration strategies. • Snowflake Architecture & Strategy • Snowflake-centric data platform • Data Pipelines: Design and build reliable, performant ETL/ELT pipelines and Reverse ETL workflows for batch, streaming, and real-time data ingestion. • Data Pipelines • ETL/ELT pipelines • Reverse ETL • Snowflake Cortex Implementation: Leverage Snowflake Cortex for AI/ML workloads, including semantic models, LLM agents, and embedded analytics. • Snowflake Cortex Implementation • Snowflake Cortex • Analytics Enablement: Develop data models, semantic views, and transformations for both online (real-time) and offline analytical workloads, facilitating business intelligence and predictive analytics. • Analytics Enablement • Performance & Optimization: Continually monitor, optimize, and tune Snowflake data systems for high scalability, reliability, and cost efficiency. • Performance & Optimization • Snowflake • Collaboration & Governance: Partner with cross-functional teams to implement best practices around data security, quality, governance, and compliance. • Collaboration & Governance • Thought Leadership: Serve as the organization's go-to expert for emerging data engineering trends, LLM applications, and Snowflake capabilities, providing strategic direction and mentorship to team members. • Thought Leadership