Lead Data Engineer (DevOps/MLOps)
Allianz
As Lead Data Engineer (MLOps), you will define the technical direction and lead cloud-based Data Science product delivery within an agile, cross-functional team. You will raise engineering practices, implement MLOps standards, and mentor data engineers while hands-on coding and shaping scalable architectures. You’ll collaborate with architects and external Azure experts to ensure robust CI/CD, monitoring, and deployment of models. This is a mission-driven role focused on delivering business value through scalable data science products and best practices. Join Allianz to shape how Data Science is delivered at scale in a hybrid, flexible environment.
Pay / Benefits- Flexible benefits
- Hybrid working
- Annual performance bonus
- Contributory pension
- Development days
- Discounts on insurance products (car, home, pet)
- Define and drive MLOps standards across CI/CD, containerisation, monitoring, alerting, testing and deployment
- Write high-quality, production-grade Python pipelines and services serving billions of requests
- Lead delivery and continuous improvement of Data Science products that support MLOps processes
- Implement best practices to build Data Science products with real business value
- Mentor and develop Data Engineers from junior to senior levels
- Collaborate with architects, engineers and external Azure experts
- Design, build and improve scalable data workflows and processes
- Champion Data Science and MLOps best practices across the business
- Maintain data governance aligned with internal policies and external regulations
- Identify opportunities to improve ways of working and drive positive change
- 5+ years in Data/ML/Platform Engineering with strong MLOps experience
- Proficiency in Python and SQL
- Hands-on experience with Kubernetes and Docker
- Cloud experience designing ML products/pipelines in Azure, AWS or GCP
- Ability to design simple solutions for complex problems
- Deep understanding of SDLC, DevOps and MLOps for CI, testing and deployment
- Comfort with ambiguity and challenging status quo
- Strong relationship-building with technical and business stakeholders
- Ability to explain complex topics to non-technical audiences
- Familiarity with data protection, consumer duty and relevant legislation
- Collaborative mindset
- Strategic thinking with hands-on practicality
- Excellent communication to non-technical stakeholders
- Azure cloud services
- Python
- SQL
Reference: WJ-747_30424466