Data Engineer Aws - Remoto

buscojobs España; Huelva; A distancia; EUR 45.000 - 70.000; Jornada completa

Descripción de la vacante

A leading company is seeking a Senior Data Engineer with MLOps expertise to help build a modular platform that supports various verticals. Responsibilities include designing data pipelines, automating the ML lifecycle, and ensuring data quality and governance, all while working remotely from Spain. Ideal candidates will have robust experience in cloud technologies and MLOps tools, contributing to a culture of collaboration and continuous learning.

Servicios

Extra day off for your birthday (paid)

Free coffee, tea, and drinks

Formación

• Experience with MLOps tools and cloud platforms is essential.
• Proven ability to design and implement data pipelines.
• Strong background in data governance and cloud-native services.

Responsabilidades

• Design, build, and maintain data pipelines for analytics.
• Develop automated pipelines for machine learning models.
• Deploy and monitor models in production environments.

Conocimientos

Data Pipeline Design

MLOps

Automation

Data Governance

Cloud Technologies

Herramientas

MLflow

TensorFlow

PyTorch

Scikit-learn

Kubernetes

Docker

Terraform

Descripción del empleo

We are looking for a Senior Data Engineer with MLOps to join Service Club as we transition into a knowledge and data intelligence company, empowering drivers and the industries that rely on them. You’ll be pivotal in building and scaling our modular platform, which supports multiple independent verticals while ensuring a seamless client experience and scalable operations.

Service Club is evolving into a knowledge and data intelligence company. Our platform, designed as a modular system with independent verticals (Academy, Jobs, and more), is interconnected through a shared intelligence layer, embodying principles of scalability, flexibility, and customer-centric design. As a Data Engineer with MLOps expertise, you will be crucial in:

1. Design and Development of Data Pipelines: Design, build, and maintain data pipelines that integrate information across internal products, ensuring consistency, scalability, and availability for analytics and product features.
2. Automation of the Machine Learning Lifecycle: Develop automated pipelines to train, validate, and deploy machine learning models that enhance product capabilities, ensuring their long-term reliability and maintainability.
3. Implement data and model workflows: Enable seamless communication between products, supporting interoperability and shared access to core services and intelligence.
4. Model Deployment and Monitoring in Production: Deploy machine learning models into production environments, monitor their performance, and ensure they remain stable, accurate, and aligned with business goals.
5. Data and Model Governance, Quality, and Security: Ensure end-to-end traceability, security, and quality of data and models in production by applying best practices in versioning, access control, and regulatory compliance.

Collaboration: Work closely with product management, design, backend, and data teams to create user-centric solutions.

Guide junior and mid-level engineers, fostering a culture of continuous learning and growth.

MLOps Tools: MLflow, TensorFlow, PyTorch, Scikit-learn.

Cloud Expertise: Kubernetes, Microservices, REST, OpenAPI, AWS, Docker, Containers, Terraform, CI/CD, Prometheus, Grafana, IaC, GitOps, Zero Trust, Automation.

Methodologies: Agile, DDD, SOLID principles.

Location: Remote work from Spain!

Perks include:

• Extra day off for your birthday (paid).
• Free coffee, tea, and drinks to stay energized.

Our process is agile, engaging, and personal:

1. A cultural and technical introduction.
2. Optional in-person visit if nearby; otherwise, meetings online.