Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.

Snowflake redefined the data landscape over a decade ago by building the AI Data Cloud—delivering industry-leading performance and price at scale across data engineering, analytics, and AI/ML workloads. Every day, new customers begin their journey to Snowflake, but migrating existing data and applications from legacy platforms remains a complex, high-effort challenge. Customers must adapt their entire ecosystem—data, database code, ETL pipelines, and consuming applications—to fully realize Snowflake’s value. The Migrations organization serves as the catalyst for this modernization, building solutions that enable customers and partners to migrate efficiently and with less risk. Within this charter, the SnowConvert AI team delivers an AI-driven migration product that moves data-centric applications to Snowflake an order of magnitude faster than industry norms. SnowConvert goes beyond schema and SQL translation, seamlessly migrating data, code, ETL pipelines, and BI tools by combining AI-based conversion with rigorous execution-level validation, ensuring that migrated systems are not only syntactically correct, but semantically equivalent to their source and production-ready on the Snowflake AI Data Cloud

RESPONSIBILITIES:

• The team develops fundamental code conversion techniques, robust data migration and validation pipelines, and automatic testing components. These capabilities are then leveraged by automated AI agents that process a complete application migration to Snowflake.

• Develop the foundations that AI agents rely on for fast, consistent code conversion

• This development team sits at the center of the original SnowConvert team, AI team, FDE to deliver the architecture below.

• Careful API design is a must for an ever-changing landscape of AI capabilities.

• Iterating with the FDE team enables quick feedback to prototypes, early products.

OUR IDEAL SOFTWARE ENGINEER WILL HAVE:

• Strong software engineering experience in Python, with a focus on performance, reliability, and distributed systems.

• Hands-on experience building agentic AI applications, especially in domains such as computer control or code gen.

• Track record of contributions to open-source agentic frameworks such as LangChain, AutoGen, etc.

• Deep understanding of distributed systems, API design, and backend architectures.

• High agency—ability to take ownership, navigate ambiguity, and independently push projects forward.
  

STRONGLY DESIRED:

• Experience with GoLang for high-performance backend services.

• Strong understanding of big data transformation, ETL, and ELT pipelines.

• Proficiency in Spark, Airflow, dbt, Kafka or other data engineering tools.

• Familiarity with streaming architectures, event-driven systems, and async processing.

• Experience optimizing large-scale data pipelines for performance and cost efficiency.

• Former founding engineers who have built and owned significant technical projects are highly valued.
  

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com