About the job
Industry Insight
Transportation logistics is the foundational industry that powers everything we rely on daily, yet it remains a complex and fragmented domain ripe for technological revolution. The US transportation logistics industry alone is an $800 billion market.
Alvys is not just participating in this change; we are driving it as the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to truly transform this essential sector.
Your role will be at the forefront of automating and standardizing a sector that moves trillions of dollars' worth of goods annually, predominantly by truck, but still lacks modern tools and solutions. Your leadership will help bridge this gap, bringing innovative technologies to a traditionally underserved and mission-critical industry.
About Alvys
Alvys is the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to dominate and truly revolutionize the $800 billion US transportation logistics industry.
We're not just iterating on old tools; we're building a world-class, multi-tenant SaaS platform from the ground up to automate, standardize, and transform this essential sector. Join us to apply your technical vision to one of the economy's most mission-critical and underserved markets, making a massive, tangible impact on the movement of global goods.
This is where industry experience meets cutting-edge technology to create the undisputed market winner, and you will be a core part of that journey.
About The Role
As a 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.
Our Tech Stack
- Data Platform: Snowflake (Warehouse, Cortex AI/ML, Semantic Models, LLM Agents)
- Data Pipelines: dbt, Fivetran, Reverse ETL (Census)
- AI/ML: Snowflake Cortex, OpenAI, Azure Cognitive
- Backend/Infra: .NET/C#, Python, Azure Ecosystem, GitHub Actions
Key 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.
The Experience You Have
- 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.
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.
- Pragmatism: You believe technical debt is a strategic choice. You choose solutions that scale and solve real problems over theoretical "perfection."
- Simplicity: You prioritize modularity and clean design to reduce cognitive load in a complex logistics domain.
- Transparency: You democratize data. You ensure insights are accessible across the organization and participate in constructive feedback loops.
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