Lead Data Engineer (MLOps) - Cloud & CI/CD Leader

Allianz UK; Greater London; Hybrid; GBP 72,000 - 88,000; Full time

Benefits offered by this job

Flexible benefits

Hybrid working

Annual performance bonus

Pension scheme

Development days

Discounts on Allianz products

Job summary

Allianz UK Personal is seeking a Lead Data Engineer (MLOps) to shape our technical direction and drive cloud-based Data Science products. You will write production-grade Python, guide architecture, and improve deployment practices while mentoring a team of Data Engineers.

The role is hybrid with offices in London, Bristol or Bournemouth. You’ll work with Azure, Kubernetes, Docker and Databricks to deliver scalable ML/data solutions across the business.

Qualifications

• 5+ years’ experience in a Data/ML/Platform Engineering role with strong MLOps expertise.
• Proficient in Python and SQL programming.
• Experience with cloud services (Azure, AWS or GCP) and data/ML product delivery.
• Hands-on coding with scalable Data Science pipelines and platforms.

Responsibilities

• Define and drive adoption of MLOps standards across CI/CD, containerisation, monitoring and deployment.
• Write high-quality Python code for production pipelines serving billions of requests.
• Lead delivery and continuous improvement of Data Science products supporting MLOps processes.
• Mentor Data Engineers from graduate to senior levels.
• Collaborate with architects and external experts from Microsoft Azure.

Skills

MLOps

Python

SQL

Cloud services

Data engineering

Tools

Azure

Kubernetes

Docker

Terraform

Databricks

Azure DevOps / GitHub

Job description

Allianz UK Personal is seeking a Lead Data Engineer (MLOps) to shape our technical direction and drive cloud-based Data Science products. You will write production-grade Python, guide architecture, and improve deployment practices while mentoring a team of Data Engineers.

The role is hybrid with offices in London, Bristol or Bournemouth. You’ll work with Azure, Kubernetes, Docker and Databricks to deliver scalable ML/data solutions across the business.