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ShippyPro

Data Platform Engineer, Mid-level

ShippyPro

. Read and assess existing CI/CD pipelines to determine whether tasks require adaptation or new work .

Posted 9/21/2026full-timeRemote • ItalyJuniorMid-Level💰 €33,000 - €43,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in CI/CD pipeline development and infrastructure-as-code, with a strong focus on data engineering and governance standards. Proficient in Python and SQL, with experience in cloud environments, particularly AWS.

Highest-signal resume keywords
CI/CD Pipeline DevelopmentInfrastructure-As-Code (IaC)Python ProficiencySQL ProficiencyDocker Experience

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
CI/CD Pipeline DevelopmentInfrastructure-As-Code (IaC)Python ProficiencySQL ProficiencyDocker Experience
Soft Skills
CollaborationProblem-SolvingDocumentation
Tools & Technologies
AWSAI Tools (Copilot, Claude, Cursor)
Industry Keywords
Data EngineeringGovernance StandardsAccess ControlRetention Policies

Tech Stack

Tools & technologies
AWSCloudDockerPythonSQL

About the role

Key responsibilities & impact
  • Read and assess existing CI/CD pipelines to determine whether tasks require adaptation or new work
  • Extend infrastructure-as-code following repository patterns
  • Apply data engineering and governance standards, including naming conventions, access control, and retention
  • Build self-serve tooling from existing patterns
  • Create and own a template repository with CI, IaC, and governance pre-wired
  • Develop modules that make creating a new pipeline a one-command job
  • Write practical documentation
  • Own the access-request flow for data resources
  • Own the template repository and IaC modules and make roadmap decisions
  • Report to the Data Team Leader
  • Collaborate across data engineering, backend, and infrastructure work

Requirements

What you’ll need
  • Independently owned a deployment path end to end, including writing the pipeline, fixing production issues, and writing the runbook
  • Ability to open unfamiliar code, explain what it does, and identify likely failure points
  • Approximately 2 years of professional experience
  • Python and SQL proficiency for daily work
  • Docker experience
  • Cloud exposure; AWS should not be a new concept
  • Comfort moving between data engineering, backend, and infrastructure work
  • Ability to use AI tools such as Copilot, Claude, or Cursor and defend the generated output
  • This is not a frontend or ML research role; no model training is required

Benefits

Comp & perks
  • 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