Data Platform Engineer – Mid-level

🕒 October 4

🌏 Anywhere in the World

💵 €33k - €43k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🚰 Data Engineer

🚫👨‍🎓 No degree required

👻 Ghost score 0%

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ShippyPro

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

📦 Logistics

☁️ SaaS

🛍️ eCommerce

💰 $15M Series B - ShippyPro on 2023-11

Logistics • SaaS • eCommerce

ShippyPro is an all-in-one shipping management platform for e-commerce and retail businesses. It centralizes multi-carrier shipping operations—connecting 190+ carriers across 160+ countries—so teams can create labels, compare rates, track shipments, manage returns, and automate fulfillment workflows via a web platform and RESTful APIs. ShippyPro offers integrations with ERPs/WMS/OMS and major e-commerce platforms, enterprise onboarding and security (SOC 2 Type II, GDPR), analytics/financial intelligence, and features designed to reduce shipping costs and improve delivery experience at scale.

📋 Description

• Read and evaluate existing CI/CD pipelines to determine task requirements • Adapt existing CI/CD patterns for new tasks • Extend infrastructure-as-code according to repository patterns • Apply data engineering and governance standards to new services, including naming conventions, access control, and retention • Build self-serve tooling from existing patterns • Create a template repository with CI, IaC, and governance pre-wired • Develop modules that make creating a new pipeline a one-command job • Write documentation that answers common questions without relying on an engineer • Own the access-request flow for data resources • Own the template repository and IaC modules and guide their roadmap

🎯 Requirements

• Independently owned a deployment path end to end, including writing the pipeline, fixing production issues, and documenting the runbook • Ability to open unfamiliar code, explain what it does, and identify likely problems • Approximately 2 years of professional experience • Python and SQL proficiency for daily use • Docker experience • Enough cloud exposure that AWS is not a new concept • Comfortable moving between data engineering, backend, and infrastructure work • Willingness to use AI tools such as Copilot, Claude, or Cursor and defend their output • This is not a frontend role and has no frontend component • This is not an ML research role and does not involve training models

🏖️ Benefits

• Meal vouchers (office or remote) • Mental health support & fitness benefits • Yearly learning budget and AI tools • Remote flexibility with expenses-paid trips to HQ for team meetups • No clock-in/out policy • One-time home office allowance • Birthday Time Off — one extra day off • Career Growth Program — clear growth paths, structured goals, and continuous feedback

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