Software Engineer, Data Transformation
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Officially a four-stage engineering process over two to four weeks (reports stretch to six): a 30-minute recruiter and/or hiring-manager screen — Snowflake hiring managers are unusually hands-on and your future manager may be your first call — then live 60-minute technical interviews (many pipelines, especially early-career, insert a 90–120-minute HackerRank/CodeSignal assessment of 2–3 medium-hard problems plus SQL), then a 3–5-round panel of coding, infrastructure-flavored system design, and behavioral 'values'/collaboration interviews (IC3+/senior adds a 30-minute tech talk), ending in a debrief with a decision typically within days. Coding skews harder than typical big-tech — graphs, DP, and especially concurrency — design leans on database internals, and the values round centers on ownership.
Read the full Snowflake interview process →Description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We're hiring Software Engineers for our Data Platform team to build and evolve Snowflake's real-time stream processing and data transformation platform. If you've built or researched high-throughput streaming systems or scalable transformation engines - in industry or graduate work - we want to talk.
AS A SOFTWARE ENGINEER, DATA PLATFORM AT SNOWFLAKE, YOU WILL:
Design and implement low-latency stream processing and in-flight data transformation systems at global scale
Own correctness and performance of streaming execution (watermarks, exactly-once delivery, out-of-order handling)
Build transformation primitives and operators that run reliably at cloud-scale throughput
Contribute to architectural decisions for our next-generation streaming and transformation platform
Write production-quality systems code and collaborate across product and engineering teams
OUR IDEAL CANDIDATE WILL HAVE:
BS/MS/PhD in Computer Science or related field — graduate research in streaming, distributed systems, or query/transformation engines is a strong differentiator
Deep distributed systems fundamentals: fault tolerance, consistency, state management
Hands-on or experience with stream processing or transformation systems (Flink, Kafka Streams, Spark Structured Streaming, or similar)
Proficiency in Java, Scala, C++, or Python
Familiarity with AI-native software engineering and agentic development workflows
BONUS POINTS FOR:
Published research or thesis in streaming, real-time transformation, or distributed computation
Experience with stream processing engine internals (e.g., state backends, checkpointing, runtime, or operator development) in systems like Apache Flink, Spark Structured Streaming, or similar.
Experience with SQL engine internals: 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
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