Our partner is looking for a Data Platform Engineer (Mid-level) based in Spain. In this role, you will help transform an established data and machine learning platform into a scalable, self-service environment that empowers engineering teams to work independently. You will build and improve deployment pipelines, infrastructure-as-code modules, and reusable tooling that makes data services easier to launch, manage, and maintain. Working across data engineering, backend development, and infrastructure, you will contribute to reliable systems that support a global shipping and fulfillment platform. You will join an experienced Data & AI team with established engineering standards, giving you a solid foundation to make a tangible impact from your first weeks. Analyze existing deployment pipelines, determine the requirements of new tasks, and adapt established workflows to support reliable, repeatable software delivery.
Apply data governance standards: Implement naming conventions, access controls, retention policies, and other governance requirements for new data services and infrastructure.
Own data access workflows: Design and manage access-request processes for data resources, reducing bottlenecks and enabling teams to obtain the permissions they need efficiently.
Work with data engineers, backend engineers, and infrastructure specialists to improve platform reliability and make shared tools useful across teams.
Deployment ownership: Demonstrated experience independently owning a deployment path end to end, including building a pipeline, troubleshooting failures, resolving production issues,



and documenting the solution in a runbook.
Approximately two years or more of professional experience in software, data, platform, DevOps, or infrastructure engineering.
A degree in Computer Science, Engineering, or a related field.
Python and SQL: Practical working knowledge of both languages and the ability to use them regularly in professional engineering tasks.
Experience working with deployment pipelines and infrastructure-as-code practices, with the ability to understand, adapt, and improve existing implementations.
Code analysis and troubleshooting: Ability to navigate an unfamiliar codebase, explain how it works, identify potential failure points, and make sound technical judgments.
Containers and cloud: Experience with Docker and familiarity with cloud computing concepts, particularly AWS. Willingness and ability to work across data engineering, backend systems, and infrastructure rather than focusing exclusively on one area.
Comfortable using AI coding assistants such as Copilot, Claude, or Cursor. You must be able to review generated code critically, explain why it is correct, and recognize when it is inaccurate or unsafe.
Remote flexibility: Work remotely from anywhere worldwide, with company-funded trips to headquarters for team meetups.
Meal vouchers available to remote and office-based employees.
An annual learning budget to support professional growth and technical development.
Home office allowance: Adaptable working approach: Collaborate with colleagues in a fast-moving environment that values high-quality engineering, ownership, and continuous improvement.

📌 Data Engineer con AWS - REMOTO (España)
🏢 Jobgether
📍 España