Staff Software Engineer - Data Sync Team

Requirements

• Built a platform multiple teams used: Owned a piece of platform infrastructure across multiple consuming teams in a company of comparable scale. Not single-team delivery. Actual platform leverage.
• Configuration frameworks or abstraction tooling: Shipped configuration frameworks or abstraction layers that other engineers adopted by default. Knows where abstractions help and where they leak.
• Data movement at scale: Production experience with sync, CDC, replication, or warehouse pipelines. End-to-end ownership from design through to running it in production.
• Cross-team consulting that landed: Worked with engineers in other teams to shape their decisions without formal authority. Comfortable holding the long-term architecture and the immediate deliverable at the same time.
• Set tech

Benefits

Additional Information

Join the team redefining how the world experiences design. Hey, hello, hiya, g'day, mabuhay, kia ora, 你好, hallo, vítejte! Thanks for stopping by. We know job hunting can be a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point. Where and how you can work Our flagship Sydney campus is uniquely Canva - an extension of our Surry Hills neighbourhood. It's a thoughtfully designed space with plenty of room to collaborate, focus, and connect. This role is based in Sydney, and we're looking for someone who calls it home. Our hybrid way of working gives you the flexibility to work remotely, and to come together on campus for meaningful in-person collaboration and connection when it matters most. We trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals. What you'd be doing in this role The Data Sync team owns the data-movement layer of Canva's platform. Every first-party event a user generates and every third-party signal that flows in from external partners runs through pipelines this team builds. Every data egress to downstream platforms runs through here too. CDC, snapshots, streaming, batch. The whole movement layer. The volume is real and growing fast. The strategic bet is moving from "land then transform" to streaming-native, AI-aware data movement. Data movement is the layer every product, ML, and analytics team builds on, and the speed at which data moves determines what those teams can ship. The team launched a Flink-based streaming pattern earlier this year together with a lakehouse architecture on S3 with Iceberg tables. The transformation happens in flight, faster, cheaper, closer to real time. Early returns are significant, with several million dollars a year in projected savings. What the team needs you to own is the technical vision for streaming-native data movement. The outcome is defined. The technical path is open. You'll decide what consolidates and what stays, what the migration sequence looks like, and what new patterns AI agents need now that the downstream consumer is increasingly an agent rather than a dashboard. The architectural calls made here become how Canva moves data for years. At the moment, this role is focused on: Owning configuration frameworks. The team's core configuration frameworks and abstraction tools are the substrate every downstream consumer touches. Evolving them is the central technical job. Shipping the streaming modernisation. Flink, Kinesis, outbox patterns, Iceberg. Getting the modernisation goal across the line without destabilising the product, ML and analytics teams that depend on it. Defining paved roads for data movement. What does a self-service ingestion pipeline look like at Canva's scale. What does a self-service egress pipeline look like. Building the patterns other teams adopt rather than reinvent. Consulting across teams. Sitting with product, ML and analytics teams to map their data movement needs, then shaping the platform so they build less themselves. Internal developer advocacy is part of the job, not an extra. Co-designing the team roadmap. Working alongside the engineering lead to shape what the team takes on next, what it deprecates, and what good looks like twelve months out. Lifting the craft level. Mentoring the existing IC team on platform engineering practice. Not formal coaching. Technical lifting through code review, design feedback and how the team handles its hardest decisions. Patterns that compound. One well-built pipeline pattern here becomes how a dozen downstream teams ship data tomorrow. Small team, org-wide leverage. What success looks like. Twelve months in, the technical standards for data movement at Canva are set. Engineering effectiveness across the Data Platform group is measurably higher than it was when this person joined. The streaming modernisation goal has landed, with downstream consumers either on the new pattern or with a credible migration path. This person is the trusted consultant across teams on Data Sync craft. The engineer other groups call when they're designing something data-shaped. You're probably a match if

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