Senior DevOps Engineer
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Job Location:
Cluj-Napoca - Romania
Monthly Salary:
Not Disclosed
Posted on:
13 hours ago
Vacancies:
1 Vacancy
Job Summary
This role is responsible for designing implementing managing and optimizing the infrastructure automation pipelines and workflows that support the entire lifecycle of software development data processing Analytics and machine learning model deployment. This individual will be a key technical expert ensuring the reliability scalability efficiency and speed of our development data analytics and ML operations fostering collaboration between teams and promoting best practices across DevOps DataOps and MLOps domains.
Heres what youll be doing:
- Design build and maintain robust CI/CD pipelines for software applications data transformations (ETL/ELT) and machine learning models (training validation deployment).
- Implement and manage Infrastructure as Code (IaC) using tools like Terraform to ensure reproducible and scalable environments (cloud or on-premise).
- Develop and automate data quality checks data pipeline monitoring and alerting systems within the DataOps framework.
- Establish and manage MLOps workflows including experiment tracking model versioning automated model retraining and performance monitoring (drift bias detection).
- Implement comprehensive monitoring logging and alerting solutions across all systems and pipelines (applications data flows ML models).
- Collaborate closely with software developers data engineers data scientists and analysts to understand their needs and provide operational support and tooling.
- Champion and enforce best practices in security reliability and performance across all operational domains.
- Troubleshoot and resolve complex infrastructure pipeline and deployment issues.
- Evaluate and recommend new tools and technologies to improve operational efficiency and capabilities.
These objectives are not exhaustive and will evolve according to identified needs and current projects.
Qualifications :
- Deep expertise in DevOps DataOps and MLOps principles practices and tooling.
- Mastery of CI/CD pipeline design and implementation for diverse artifacts (code data models).
- Strong proficiency in cloud infrastructure management and automation (Azure).
- Expertise in containerization and orchestration (Docker Kubernetes).
- Strong scripting and automation skills (Python Bash etc.).
- Experience with monitoring logging and observability tools (e.g. Prometheus Grafana ELK Stack Datadog).
- Understanding of data engineering concepts and data pipeline orchestration tools.
- Familiarity with ML model lifecycle management and associated tooling.
- Bachelors or masters degree in computer science Engineering or a related field.
- 5 years of experience in technical operations roles with deep expertise in DevOps and demonstrable hands-on experience implementing DataOps and MLOps practices.
- Proven experience with cloud platforms (mainly Azure AWS is a plus) containerization (Docker Kubernetes) CI/CD tools (e.g. Jenkins GitLab CI ArgoCD) IaC tools (e.g. Terraform) scripting (Python Bash) data pipeline orchestration (e.g. Airflow) and ML platforms (e.g. MLflow Kubeflow SageMaker/Vertex AI).
- English or French Level: fluent
Additional Information :
- Access to modern tools and technologies.
- A chance to make a meaningful impact on enterprise product quality.
- Opportunities for career growth and development.
- Soft skills and Technical Trainings Workshops Conferences and attendance of different similar events
Remote Work :
No
Employment Type :
Full-time
Key Skills
- APIs
- C/C++
- Computer Graphics
- Go
- React
- Redux
- Node.js
- AWS
- Library Services
- Assembly
- GraphQL
- High Voltage
About Company
Welcome to Generix, a leading provider of SaaS solutions that simplify and revolutionize global collaboration across the supply chain. We empower businesses worldwide to responsibly streamline the exchange of goods and data throughout the entire supply chain. Our innovative digital se ... View more
