Data Engineer - AWS | Teletrabajo

Service Club; Almería; A distancia; EUR 50.000 - 75.000; Jornada completa

Descripción de la vacante

Service Club is seeking a Senior Data Engineer with MLOps expertise to transform data operations and enhance product capabilities. In this role, you’ll design data pipelines, automate ML workflows, and ensure data governance within a collaborative environment. We value continuous learning, offering benefits like remote work flexibility and an extra day off to celebrate your birthday.

Servicios

Extra day off for birthdays

Free coffee, tea, and drinks

Formación

• Proven experience in MLOps and data engineering.
• Strong knowledge of data pipelines and governance.
• Experience with machine learning frameworks and cloud services.

Responsabilidades

• Design and maintain data pipelines for analytics.
• Automate the machine learning lifecycle for product enhancements.
• Deploy and monitor ML models in production enforcing quality standards.

Conocimientos

MLOps

Data Governance

Data Quality

Interoperability

Automation

Educación

Bachelor’s in Computer Science or related field

Herramientas

MLflow

TensorFlow

PyTorch

Scikit-learn

AWS

Docker

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, revolutionizing the delivery and mobility sector.

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, 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 across products, continuously 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 across the product ecosystem.

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

Guide junior and mid-level engineers through their development journey while fostering a culture of continuous learning and growth.

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

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

Knowledge of Agile, DDD, SOLID principles.

Remote work from Spain!

Extra day off – Celebrate your birthday with a paid day off.

Free coffee, tea, and drinks – Stay energized throughout the day.

Our process is agile, engaging, and personal:

A cultural and technical introduction.

Meet us in person (optional): If you’re in the area, drop by our office! Otherwise, we’ll meet online.