Senior Data Engineer (MLOps Engineer) in Bournemouth

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 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.

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

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

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, deploy, and orchestrate Docker containers, optimizing for performance and resource utilisation.
• Design, build and maintain cloud R&D solutions using IaC tools like Terraform.
• Build, improve and maintain monitoring systems to track model performance and infrastructure health, ensuring reliability, scalability, and security of ML systems.
• Develop CI/CD 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 tickets and collaborating with team members and across disciplines to deliver products; communicate technical decisions and findings to both technical and non‑technical audiences.
• Stay current with the newest cloud and data tech and contribute to continuous improvement across cloud tooling, engineering standards, and platform development.

Essential and Desired Skills

• Experience deploying, monitoring and maintaining production services.
• Hands‑on containerisation (Docker) and orchestration (Kubernetes or similar).
• Managing and maintaining real‑time endpoints or APIs.
• Automated deployment into production environments.
• Cloud & infrastructure engineering: building or supporting cloud infrastructure for data or predictive services; expertise in Terraform, Azure preferred or other public cloud platforms; infrastructure patterns for scalable, secure services; CI/CD automation.
• Experience with Azure DevOps or GitHub Actions.
• Automated testing, packaging and deployment processes.
• Data engineering experience: SQL proficiency, familiarity with PySpark beneficial, dbt, Microsoft Fabric, SQLMesh.
• Strong Python skills with good documentation and unit testing practices.
• Comfortable in an agile delivery environment and able to communicate clearly with non‑technical teams.
• Demonstrates curiosity, continuous learning, and a collaborative mindset.

Desirable: Understanding of GDPR and data governance; experience in insurance or financial services; familiarity with LLMs; knowledge of infrastructure monitoring, backup, or disaster recovery.

Benefits

• Flexible buy/sell holiday options.
• Hybrid working.
• Annual performance‑related bonus.
• Contributory pension scheme.
• Development days.
• Discount up to 50% on a range of insurance products including car, home and pet.
• Retail discounts.
• Volunteering days.

Working Hours and Flexibility

We support hybrid work patterns and offer flexible working hours. If you need flexibility, let us know as part of your application and we’ll do what’s feasible.

Commitment to Equality

We are an equal‑opportunity employer and welcome applications from all. We are committed to an inclusive workforce and support candidates with disabilities or long‑term health conditions with tailored adjustments.

Closing Date 26/03/26