Senior Data Engineer

Alvys

32d

About The Position

As a Staff Data Engineer, you will be the primary architect of our data ecosystem. Alvys is shifting toward a Snowflake-centric data architecture to power our next generation of logistics intelligence. You aren't just building pipelines; you are defining our LLM-based data strategy, enabling large-scale ML model deployment, and leveraging Snowflake Cortex to turn fragmented logistics data into actionable AI-driven products.
This is a high-visibility, 'player-coach' position. You will work closely with leadership to ensure our data infrastructure supports real-time operational needs today while scaling for the AI-first logistics world of 2026 and beyond.

Requirements

• 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).
• Expert-level skill in SQL and Python. Extensive experience with dbt and modern orchestration (Airflow/Dagster).
• Demonstrated experience building pipelines for ML or LLM-based applications, including feature engineering and model deployment.
• Competency in Azure (preferred) or other major cloud providers, including CI/CD and infrastructure-as-code principles.
• Experience driving cross-team consensus on architectural decisions and mentoring junior/mid-level engineers.

Responsibilities

• Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications.
• 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.
• Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale.
• Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed