At a Glance
- Tasks: Build and maintain data and machine-learning systems for impactful business decisions.
- Company: Join a forward-thinking tech company with a collaborative and agile culture.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Shape the future of data technology while working on high-impact projects.
- Qualifications: Experience in deploying production services and containerisation technologies.
The predicted salary is between 60000 - 60000 £ per year.
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, deploy, and orchestrate docker containers, optimizing for performance and resource utilization.
- Design, build, and maintain cloud R&D solutions using IaC tools like Terraform.
- Build, improve, and maintain 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.
- 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:
- Experience deploying, monitoring, and maintaining production services.
- Hands‑on experience with containerisation (Docker) & service orchestration (Kubernetes or similar).
- Managing and maintaining real‑time endpoints or APIs.
- Automated deployment into production environments.
Senior Data Engineer (MLOps Engineer) in London employer: Allianz
At Munich Re Specialty – Global Markets, we pride ourselves on being an exceptional employer that fosters a culture of support, innovation, and inclusivity. Our commitment to employee growth is reflected in our comprehensive benefits package, including generous annual leave, a non-contributory pension, and opportunities for professional development. Located in a vibrant community, we not only focus on individual success but also encourage our team to engage in local initiatives, making a meaningful impact both within and outside the workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (MLOps Engineer) in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Allianz!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer (MLOps Engineer) at Allianz.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Allianz.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer (MLOps Engineer) at Allianz, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer (MLOps Engineer) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Allianz, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Allianz. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Allianz
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Allianz!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
