Data Platform Engineer – Mid-level

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 €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 assess existing CI/CD pipelines to determine whether tasks require adaptations of established patterns • Extend infrastructure-as-code following repository patterns • Apply data engineering and governance standards to new services, including naming conventions, access control, and retention • Build self-serve tooling, including a template repository with CI, IaC, and governance pre-wired • Create modules that make new pipelines a one-command job • Write documentation that answers common questions without requiring engineer assistance • Own the access-request flow for data resources • Own the template repository and IaC modules, including the roadmap and documentation • Collaborate across data engineering, backend, and infrastructure within the Data & AI team • Report to the Data Team Leader

🎯 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 issues • Approximately 2 years of professional experience • Proficiency in Python and SQL for daily work • Experience with Docker • Cloud exposure; AWS should not be a new concept • Comfort working across data engineering, backend, and infrastructure • Ability to use AI tools such as Copilot, Claude, or Cursor and defend the correctness of generated output • No frontend development experience required; this is not a frontend role • No ML research or model-training experience required

🏖️ 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 with clear growth paths, structured goals, and continuous feedback • International team