ppWe have built a data and ML platform that actually works: pipelines, infrastructure-as-code, deployment paths, governance standards baked in. /ppNow we need someone to turn that foundation into something any engineering team can build on directly, without waiting on you for every request. /ppYou won't get a blank page. You'll get working patterns
- and the job is to read them, apply them, and turn them into tooling other people use without thinking twice. /ppIf you've owned a deployment path end-to-end
- written it, broken it, fixed it, documented it
- keep reading /ph3About Us /h3pShippyPro was founded in 2016 on a simple idea: make shipping effortless so businesses can focus on growth. /ppToday we power shipping for thousands of merchants across 60+ countries, and our data platform is what keeps that running at scale
- every label, every tracking update, every carrier integration leaves a trace, and our systems need to handle that without blinking. /ppWe've raised $15M (Series B) and we're scaling fast in a $9T industry still full of inefficiencies. Behind the product, there's a Data AI team building the infrastructure that makes reliability possible
- clean pipelines, sane governance, and tooling that doesn't require an engineer to babysit it. You'll work within this team, reporting to our Data Team Leader. /ppIf you like systems that reward good judgment over heroics, you'll fit right in. /ph3The Product /h3pShippyPro is a shipping and fulfillment platform that helps merchants automate the entire shipping workflow, from choosing the best carrier service to generating labels and tracking deliveries. It connects with e-commerce platforms and multiple couriers, giving teams one place to ship faster, reduce manual work, and keep full control over costs and delivery performance.



/ph3The Challenge /h3pWe're not looking for someone who's only ever worked inside a CI/CD pipeline someone else built. /ppWe're looking for someone who's built one, broken it, fixed it at 2am, and written the runbook so nobody else has to repeat that. /ppOur data platform works. The next phase is making it self-serve: a template repo that ships with CI, IaC and governance already wired, modules that make a new pipeline a one-command job, and documentation that actually answers the question instead of pointing at a person. /ppThat's the job. Not maintaining what exists
- making it something the rest of engineering can pick up without you. /ph3Why ShippyPro /h3ulliYou’ll own real infrastructure from week one
- no sandbox, no toy projects /liliBy month six, the template repo and IaC modules have your name on them: your call on the roadmap, your PRs reviewed like everyone else's /liliYou’ll move across data engineering, backend, and infrastructure
- not stuck in one lane /liliYou’ll work alongside a Data AI team that already has strong patterns in place, so you’re building on solid ground, not from scratch /liliWe use AI tools daily (Copilot, Claude, Cursor)
- and we care about whether you can defend what they produce, not just how fast you shipped it /li /ulh3What You’ll Do /h3h3From week one (~40% of the role): /h3ulliRead our existing CI/CD pipelines well enough to judge what a new task actually requires




- most of the time it's a small adaptation of something that already exists, and knowing that is the skill /liliExtend our infrastructure-as-code following the patterns already in the repo /liliApply our data engineering and governance standards to new services: naming conventions, access control, retention /li /ulh3Ramping up from month two: /h3ulliTurn those patterns into self-serve tooling: a template repo with CI, IaC and governance pre-wired, modules that make a new pipeline a one-command job, documentation that answers the question instead of pointing at a person /liliOwn the access-request flow for data resources so other teams stop queueing behind an engineer /li /ulh3By month six: /h3ulliOwn the template repo and IaC modules outright
- your name in the docs, your call on the roadmap /li /ulh3What You’ll Bring /h3h3The one thing we won't compromise on: /h3ulliYou've independently owned a deployment path end to end
- you wrote the pipeline, broke production with it, fixed it, and wrote the runbook afterwards. Having worked on a team that had CI isn't the same thing /li /ulh3Close behind: /h3ulliYou can open unfamiliar code, explain what it does, and point at what's likely to bite
- we'll test this directly /li /ulh3Beyond that: /h3ulli~2 years of professional experience, or more /liliPython and SQL you can work in daily without constantly looking things up /liliDocker, and enough cloud exposure that AWS isn't a new concept (we use SageMaker among other things, but you don't need to have touched it) /liliComfort moving between data engineering, backend, and infrastructure work rather than staying in one lane /li /ulh3Worth saying plainly, so you can self-select: /h3ulliThis isn't a frontend role, and there's no frontend compon

📌 Data Engineer con AWS (Italia)
🏢 ShippyPro
📍 Italia