Data Platform Engineer – Mid-level

ShippyPro

. Read and evaluate existing CI/CD pipelines to determine task requirements .

Posted 10/4/2026full-timeRemote • United StatesJuniorMid-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 Docker and 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

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Hard Skills

CI/CD Pipeline DevelopmentInfrastructure-As-Code (IaC)Python ProficiencySQL ProficiencyDocker Experience

Soft Skills

Problem-SolvingDocumentation Skills

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 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

What you’ll need

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

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 — clear growth paths, structured goals, and continuous feedback