Lead Data Engineer (DevOps/MLOps)

Overview

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)

Responsibilities

• 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

Key requirements

• 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

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