Staff Infrastructure Engineer - Ingestion

About the role Step into the foundation of Shopify's data platform. Imagine owning the systems that move every byte of operational data — every order, every event, every change — from Shopify's source-of-truth databases and Kafka streams into the analytics layer that powers dashboards, ML, and AI across the company. We're seeking a Staff Engineer to architect, operate, and evolve the ingestion platform that millions of merchants depend on, even if they never see it. Your work will be the substrate beneath critical analytics products at Shopify, shaping how quickly and reliably we can answer questions about our business and our merchants. Join a remote-first, AI-native team of seasoned data infrastructure engineers, ship continuously, and see your code raise the ceiling on what's possible downstream. Responsibilities Architect, optimize, and own Shopify's production ingestion platform — ingestion of data from operational databases and Kafka topics into Shopify’s analytics data store — designed for high throughput and continuous reliability at very large scale. Leverage technologies like Kafka, BigQuery, GCP, Dataflow, Terraform, and Kubernetes to deliver state-of-the-art performance and efficiency across both database and stream ingestion pipelines. Partner with database platform, streaming platform, governance, and downstream analytics teams to seamlessly land, validate, and scale data products powering our platform. Drive cost optimization and system efficiency — reducing cloud spend, source-system load, and pipeline complexity without sacrificing freshness or completeness. Lead deep technical investigations across upstream and downstream data-store internals (indexing, replication, load patterns) to apply rigorous solutions. Contribute to technical strategy and culture for the ingestion team, represent the team across Shopify, champion projects, mentor engineers across all levels, and collaborate with senior engineers across Data Platform. Participate in the team's on-call rotation, supporting production reliability for ingestion systems. Qualifications Proven, hands-on expertise in building and operating large-scale data infrastructure, with measurable wins in reliability, throughput, or cost. Deep experience close to data stores — CDC, replication, indexing, partitioning, and the behavior of operational databases under load. Strong software engineering skills (Python, Java, and/or other relevant languages) with a robust systems and distributed computing mindset. Demonstrated leadership in architecting or operating reliable data pipelines at scale. Track record of cross-functional impact: working closely with database teams, streaming platform engineers, infra, and downstream data consumers to deliver production results. Advanced understanding of streaming systems and the trade-offs between latency, throughput, and cost. Nice to Haves Experience with ingestion / streaming frameworks (Kafka Connect, Debezium, Beam, Flink, etc.) as part of a broader data infrastructure practice — not a single-product specialty. Experience optimizing pipelines across a variety of source systems (MySQL, distributed SQL like Yugabyte/Spanner/CockroachDB). Experience with modern data warehouse and lakehouse patterns (BigQuery, Snowflake, Iceberg). Prior experience in e-commerce, large-scale product infrastructure, or globally distributed data workloads. Experience maintaining Scala services. Fluency with AI coding tools (Claude Code, Cursor, etc.) as part of your daily workflow. 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.