
Data and MLOps Engineer
5 days ago
Your profile: You keep reinventing us.
Bachelor's/Master's in Computer Science, Software Engineering, or related field
3aEUR"5+ years in Data Engineering, MLOps or DevOps
Experienced in agile methodologies and cross-functional collaboration
Strong in data processing, ETL, and ML pipeline development/orchestration
Proficient in Python and SQL (clean code principles)
Hands-on with GitLab CI/CD, CI components, and automated pipelines
Deep expertise in GCP: GCS, BigQuery, CloudRun, VertexAI
Skilled in Docker, dev-containers, and microservices
Proficient with Terraform, dbt, and Airflow orchestration
Experienced in API development and modern DevOps practices
Collaborative, service-oriented team player supporting Data Science teams
Pragmatic problem-solver balancing technical and business needs
Strategic thinker with oversight in complex technical landscapes
Self-driven, organized, able to manage multiple priorities
Fully proficient in English; German preferred We're looking for a Senior Data and MLOps Engineer (m/f/d) to join Tchibo's "Machine Learning and Predictive" team, part of our Data and AI department. You'll help scale robust, production-ready ML systems and data infrastructure across strategic business areas, enabling our data-driven transformation. We design, build, and operate innovative ML services for sales and logistics, and provide end-to-end support as trusted advisors across the organization. This role reinforces our MLOps capabilities to meet growing demand, enhance deployment, and ensure operational excellence for our Data Science teams.
Develop and enhance the MLOps framework and drive adoption across ML projects
Build and maintain ETL/ML pipelines using GCP services, Airflow, and orchestration tools
Implement CI/CD processes and GitLab pipelines for automated ML deployments
Manage infrastructure with Terraform, Docker, and cloud-native GCP services
Provide technical support to Data Science teams on MLOps/DevOps practices
Monitor and optimize production ML systems for stability, performance, and scalability
Develop and integrate APIs to enable seamless data flow and model serving
Collaborate with cross-functional teams to advance ML system maturity and operational excellence
Design and maintain robust ML infrastructure and data pipeline architectures
Enhance maturity, stability, and maintainability of ML systems to support scalable growth Your benefits: Together we stay different.
Work-Life Balance: Flexible hybrid working policy, 26 vacation days + your birthday off.
Perks: Monthly transport allowance, meal tickets, health and life insurance.
Coffee Lovers Welcome: Free Tchibo coffee for home and office.
Innovative Work Culture: You'll work on impactful projects in a collaborative and open-minded team.
Diversity and Inclusion: A place where your perspectives and ideas are valued.
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