Senior Data Engineer (MLOps Engineer)

Allianz; Greater London; On-site; GBP 51,000 - 69,000; Full time

Job summary

Allianz is seeking a Senior Data Engineer to build and maintain production‑ready data and ML systems, spanning from stakeholder engagement to real‑time cloud deployments. The role emphasizes containerised infrastructure, automated pipelines, and IaC practices to support scalable data platforms.

The successful candidate will join a small stream‑aligned agile team, work with domain experts, and contribute to best practices while delivering high‑impact data products for business decisions.

Qualifications

• Experience deploying, monitoring and maintaining production services.
• Experience containerisation with Docker and service orchestration with Kubernetes or similar.
• Experience with automated deployment into production environments.

Responsibilities

• Design, build, and operate production‑level data and ML services with real-time API endpoints.
• Build, deploy and orchestrate Docker containers for scalable data platforms.
• Design, build and maintain cloud R&D solutions using IaC tools like Terraform.
• Develop monitoring to track model performance, infra health, and ensure reliability, scalability and security of ML systems.
• Develop CI/CD processes to automate workflows using tools like Azure DevOps.
• Write high‑quality Python for production data pipelines and services.
• Deliver data extracts, transformations, and features to support modelling and analytics.
• Work in an agile workflow, manage tickets and collaborate across disciplines.

Skills

Docker

Kubernetes

Real-time APIs

CI/CD

Tools

Terraform

Azure DevOps

Job description

Role Description

As a Senior Data Engineer, you will play a key role in building and maintaining production‑ready data and machine‑learning systems that support critical business decisions. You’ll work across the full lifecycle, from engaging with stakeholders and shaping data/model outputs, to deploying and maintaining real‑time services in a cloud environment.

A significant part of this role involves developing and evolving our cloud‑based infrastructure, including containerised applications, automated deployment pipelines, and infrastructure‑as‑code. You’ll also help shape engineering best practices and support the growth of modern, scalable data platforms.

You’ll join our small stream‑aligned agile team, working closely with domain experts to understand business needs and deliver high‑impact solutions.

Location:

This role is hybrid, with the option to work from our London, Bristol, or Bournemouth offices. You’ll be required to attend the office two days per month.

Salary Information

Pay: Circa £60,000 per annum, dependent on experience, skills, and location.

Salary is one part of our wider total reward package.

What You’ll Do

• Design, build, and operate production‑level data and machine‑learning services, including real‑time API endpoints that serve 10 million + requests daily
• Build and deploy and orchestrate docker containers, optimizing for performance and resource utilization
• Design, build and maintain cloud R&D solutions using IaC tools like Terraform
• Building, improving and maintaining monitoring systems to track model performance, infrastructure health and ensure reliability, scalability, and security of ML systems
• Develop CICD processes to help automate workflows using tools like Azure DevOps
• Write high‑quality, well‑tested Python for production‑grade data pipelines and services.
• Deliver data extracts, transformations, and features to support modelling and analytics.
• Work within an agile workflow, managing your own tickets and collaborating with team members and across disciplines to deliver products Communicate technical decisions and findings to both technical and non‑technical audiences.
• Taking time to stay up to date with the newest cloud and data tech as you contribute to continuous improvement across cloud tooling, engineering standards, and platform development.

About You (What We’re Looking For)

Essential Skills

1. Experience deploying, monitoring and maintaining production services

We’re looking for engineers who have worked hands‑on with:

• Containerisation (Docker) & Service orchestration (Kubernetes or similar)
• Managing and maintaining real‑time endpoints or APIs
• Automated deployment into production environments