Data Platform Engineer

Zimmer Biomet
Portsmouth
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer (Azure Data Platform)

Senior Data Engineer

Lead Data Engineer

AWS Data Engineer - Snowflake Cortex (Contract)

Data Engineer

JOB DESCRIPTION

At Zimmer Biomet, we believe in pushing the boundaries of innovation and driving our mission forward. As a global medical technology leader for nearly 100 years, a patient’s mobility is enhanced by a Zimmer Biomet product or technology every 8 seconds.

As a Zimmer Biomet team member, you will share in our commitment to providing mobility and renewed life to people around the world. To support our talent team, we focus on development opportunities, robust employee resource groups (ERGs), a flexible working environment, location specific competitive total rewards, wellness incentives and a culture of recognition and performance awards. We are committed to creating an environment where every team member feels included, respected, empowered, and recognized.


What You Can Expect


The Senior Data Platform Engineer will be responsible for the development of data platforms which serve the needs of our development teams and data products that improve the quality-of-care and quality-of-life of Orthopaedic patients worldwide. The Connected Health AI and Data Science Team’s existing platform is evolving from batch processing to cater for real-time and Generative AI solutions, the Data Platform Engineer will play a critical role in driving the growth and adoption of this platform.
 

How You'll Create Impact

Work closely with machine learning scientists and engineers to develop data serving platforms and platforms that power products on Microsoft Azure that process both real-time and batch data from diverse sources; Integration of third-party platforms and software to build a platform for the efficient onboarding and manipulation of data; Continuously identify areas for system improvements, focussing on enhacing both backend efficiency and user experience; Develop re-usable architectures and infrastructure via Infrastructure as Code for use in current and future products; Fulfilling regulatory commitments through the use of automation; Contribute to the shaping of the technological roadmap to help progress the Connected Health team;
 

What Makes You Stand Out

Proficiency in the following tools:

Python for developing data pipelines; Apache Spark for the ingestion and transformation of data; SQL databases; Data stores such as Azure Blob Storage, Azure Data Lake, S3, Azure Cosmos DB; Infrastructure as code tooling such as Terraform, Pulumi, Bicep; Git and CI/CD pipeline tooling;

Your Background

Experience/competency in the following areas:

Strong communication skills as this position works as part of a cross-disciplinary product team; Programming with Python and packages associated with the data engineering workflow; Awareness of machine learning techniques and their applications; Apache Spark and Apache Airflow for ETL pipelines; Developing applications to run on the cloud in a cloud-native way; Data pipeline, application and infrastructure monitoring with tools such as NewRelic; Familiarity with infrastructure concepts such as virtual machines and networking; Communicating analyses, technical ideas, and their value to a range of audiences; Ability to learn new technologies and methodologies;

Some experience in one of the following areas is beneficial, but not essential: 

Data quality monitoring Working with healthcare data; Working with and deploying applications to Kubernetes, Managed Container Environments; Working with Azure data tools such as Synapse or Fabric; Delivering software and/or artificial intelligence/machine learning in regulated spaces;

Travel Expectations


This role is home-based and the team embraces a culture of remote-first. The team regularly meets once every fortnight in Central London, but individuals can decide in-conjunction with the rest of their team whether to meet others in the team more or less regularly depending on their circumstances.

This role works closely with team members based in the U.S. therefore, occasional evening meetings will be required. There also may be occasional travel to the U.S. for internal meetings, and also travel in UK/Europe to meet with customers.
 


EOE/M/F/Vet/Disability

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.