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Day 6
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Work setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: FullTimeFrom the employer’s posting
Design, build and operate internal platform services and CLIs for authoring, scheduling and shipping data changes
Improve reliability and operability of data platform systems, including monitoring, incident response and runbooks
Lead large-scale migrations and deprecations with phased plans and measurable cutover criteria
Drive cost and performance outcomes by finding bottlenecks, right-sizing workloads and building guardrails
Build developer experience for data producers and consumers, such as fast feedback loops and self-serve workflows
Design, build, and operate internal platform services and CLIs that teams use to author, schedule, validate, and ship analytics and operational data modeling changes safely.
Improve reliability and operability for data platform systems: SLO-minded monitoring, incident response patterns, safe rollouts, and clear runbooks.
Lead large-scale migrations and deprecations (e.g., storage/table formats, orchestration, query engines) with a phased plan, guardrails, and measurable cutover criteria.
Drive cost and performance outcomes at scale: identify systemic bottlenecks, right-size workloads, and build guardrails that prevent expensive failure modes.
Build developer experience for data producers/consumers: fast feedback loops, golden paths, self-serve workflows, and actionable error messages.
Proficiency with at least one major cloud platform (GCP, AWS, or Azure).
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
20 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Data-change discipline: comfortable reasoning about backfills, idempotency, schema evolution, and blast radius when many downstream datasets depend on a platform behavior. - Proficiency with at least one major cloud platform (GCP, AWS, or Azure). - Bonus: hands-on experience with BigQuery, Airflow/Composer, Iceberg/Delta (or similar open table formats), data lake/lakehouse operations, or large-scale platform migrations.
- Proficiency with at least one major cloud platform (GCP, AWS, or Azure). - Bonus: hands-on experience with BigQuery, Airflow/Composer, Iceberg/Delta (or similar open table formats), data lake/lakehouse operations, or large-scale platform migrations. 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.
Complete your application on www.shopify.com. The employer’s form will show what is required.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Build the data platform that powers Shopify. Our Data Platform Tools team owns how Shopify moves, monitors, and uses data at massive scale. You’ll build the internal tooling and platform services that let thousands of engineers and analysts move, monitor, and govern analytical data safely at massive scale.
Design, build, and operate internal platform services and CLIs that teams use to author, schedule, validate, and ship analytics and operational data modeling changes safely.
Improve reliability and operability for data platform systems: SLO-minded monitoring, incident response patterns, safe rollouts, and clear runbooks.
Lead large-scale migrations and deprecations (e.g., storage/table formats, orchestration, query engines) with a phased plan, guardrails, and measurable cutover criteria.
Drive cost and performance outcomes at scale: identify systemic bottlenecks, right-size workloads, and build guardrails that prevent expensive failure modes.
Build developer experience for data producers/consumers: fast feedback loops, golden paths, self-serve workflows, and actionable error messages.
Partner across teams to standardize patterns (metadata, access, testing, promotion pipelines) while preserving escape hatches for legitimate exceptions.
You design maintainable systems, operate them responsibly in production, and reason about correctness, reliability, and performance when data and platform changes affect many teams.
Production ownership: ships changes with a plan for rollout/rollback, monitors impact, and follows through after launch.
Systems thinking: clear interfaces/contracts, explicit failure modes, and pragmatic tradeoffs between correctness, freshness, cost, and complexity.
Data-change discipline: comfortable reasoning about backfills, idempotency, schema evolution, and blast radius when many downstream datasets depend on a platform behavior.
Proficiency with at least one major cloud platform (GCP, AWS, or Azure).
Bonus: hands-on experience with BigQuery, Airflow/Composer, Iceberg/Delta (or similar open table formats), data lake/lakehouse operations, or large-scale platform migrations.
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.
Ready to build the platform behind the platform? Join us.
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