The Identity & Events Platform team sits at the heart of how Shopify moves data. The Event Refinery sub-team is building the next-generation event processing platform that will replace Shopify's legacy eventing infrastructure, becoming the central hub through which all merchant, buyer, and third-party event data flows.
The systems this team builds power personalization, recommendations, advertising, internal and external analytics, partner data sharing, and automations. The team is now scaling from roughly 10 billion events per day toward hundreds of billions as Shopify migrates teams onto the new platform. That is the problem you would be joining to help solve.
What You'll Work On
Design, build, and operate high-throughput streaming pipelines that process behavioral event data at massive scale
Ensure compliance and correctness in how event data is enriched, routed, and made available to downstream consumers
Improve pipeline reliability and observability including latency, memory optimization, Kafka throughput, and operational health
Collaborate with downstream teams (i.e. personalization, analytics, advertising, etc) to evolve the platform to meet their data needs
Participate in on-call rotations and own the operational health of production systems
What We're Looking For
Requirements:
Proven experience building and operating high-throughput data processing systems in production at meaningful scale
Proficiency in Java or a similar JVM/statically-typed language (Kotlin, Scala, Go, Rust) — our streaming pipelines are written in Java and you should be comfortable working in it or ramping up quickly.
Hands-on experience with Apache Flink or a comparable stream processing framework (Dataflow, Spark Streaming)
Working knowledge of Apache Kafka including producing, consuming, tuning throughput, and understanding operational behavior under load
Operational mindset — you have been on-call, you think about latency and memory, and you know how to run a production system, not just write code for one
Kubernetes familiarity in a production context — running workloads and owning their reliability
Strong signals we look for:
Experience with behavioral, or event data pipelines rather than transactional or reporting-focused data
Observability work including metrics, alerting, tracing, and reducing noise in production systems
Latency optimization and compression work on streaming or storage systems
Complex pipeline work such as aggregations, rollups, and enrichment beyond simple data-in/data-out
Nice to have:
Interest in data privacy and compliance at the processing layer: how to correctly aggregate, route, and act on data given consent and governance signals
Experience at companies or platforms that treat behavioral data as a core product
What This Role Is Not
This is not a data engineering role in the analytics sense. If SQL is your primary tool, this probably is not the right fit. We are looking for engineers who build the infrastructure that makes data move, not the models or dashboards that sit on top of it.
At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.
Proven experience building and operating high-throughput data processing systems; proficiency in Java or similar JVM language; hands-on with Apache Flink or comparable framework; working knowledge of Apache Kafka; Kubernetes familiarity; on-call experience.
Key Responsibilities
- building streaming pipelines
- improving pipeline reliability
- collaborating with teams
Skills & Tools
Java, Kotlin, Scala, Go, Rust, Apache Flink, Dataflow, Spark Streaming, Apache Kafka, Kubernetes
Job Details
- Category: Software Development
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — North America
- Languages: English
About Shopify
A global e-commerce platform that enables merchants to sell online. — Industry: Information Technology