Data Engineer - AWS | Teletrabajo

Service Club; Córdoba; A distancia; EUR 45.000 - 75.000; Jornada completa

Descripción de la vacante

A prominent company in data intelligence is searching for a Senior Data Engineer with MLOps expertise. The role involves designing data pipelines, automating machine learning workflows, and ensuring data quality and security. This position fosters collaboration, continuous learning, and offers a range of engaging perks, including remote work options from Spain.

Servicios

Extra day off for birthday

Free coffee, tea, and drinks

Engaging hiring process

Formación

• Experience in designing and maintaining data pipelines.
• Strong background in deploying and monitoring machine learning models.
• Familiarity with cloud infrastructure and containerization tools.

Responsabilidades

• Design and build data pipelines for internal products.
• Develop automated pipelines to deploy machine learning models.
• Collaborate with cross-functional teams to create user-centric solutions.

Conocimientos

Data Pipeline Design

Machine Learning Lifecycle Automation

Data Governance

Collaboration

Continuous Learning

Herramientas

MLflow

TensorFlow

PyTorch

Scikit-learn

Kubernetes

AWS

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 play a pivotal role 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, 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 teams 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 Tools: MLflow, TensorFlow, PyTorch, Scikit-learn.

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

Methodologies: Agile, DDD, SOLID principles.

Remote work from Spain!

Perks include an extra day off for your birthday, free coffee, tea, and drinks, and an engaging, personal hiring process involving a cultural and technical introduction, with options for in-person or online meetings.