# Software Engineer, Data Transformation

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** Unspecified
**Role:** Data Engineering
**Skills:** Stream Processing, Distributed Systems, Apache Flink, Kafka Streams, Spark Structured Streaming, Java, Scala, C++, Python, Fault Tolerance, State Management, Sql Query Optimization, Test Driven Development, Formal Verification
**Posted:** 2026-07-17

> Build and evolve Snowflake’s real-time stream processing and data transformation platform, focusing on low-latency execution, correctness, performance, and cloud-scale reliability. The role requires strong distributed systems fundamentals and experience with streaming or transformation engines.

## Job Description

## Responsibilities
- Design and implement low-latency stream processing and in-flight data transformation systems at global scale.
- Own the correctness and performance of streaming execution, including watermarks, exactly-once delivery, and out-of-order handling.
- Build transformation primitives and operators that run reliably at cloud-scale throughput.
- Contribute to architectural decisions for a next-generation streaming and transformation platform.
- Write production-quality systems code and collaborate across product and engineering teams.

## Requirements
- Bachelor's, master's, or doctorate in Computer Science or a related field; graduate research in streaming, distributed systems, or query/transformation engines is a strong differentiator.
- Strong distributed systems fundamentals, including fault tolerance, consistency, and state management.
- Hands-on experience with stream processing or transformation systems such as Flink, Kafka Streams, or Spark Structured Streaming, or similar technologies.
- Proficiency in Java, Scala, C++, or Python.
- Familiarity with AI-native software engineering and agentic development workflows.

## Nice-to-haves
- Published research or a thesis in streaming, real-time transformation, or distributed computation.
- Experience with stream processing engine internals, including state backends, checkpointing, runtime, or operator development, in systems such as Apache Flink or Spark Structured Streaming.
- Experience with SQL engine internals, including query optimization, execution plan design, storage formats, or transaction layers.
- Familiarity with Spec Driven Development (SDD) and Test Driven Development (TDD).
- Familiarity with formal verification.

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