Senior Data Engineer

Cambridge
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Do you you enjoy working closely with a tight-knit team?
Do you want to work in a business where making a difference is at the heart of their goals?

I’m supporting a rapidly scaling medical technology innovator in their search for a Senior Data Engineer to help design and build a next-generation unified lakehouse platform on Databricks. This is a fantastic opportunity for a product-minded engineer who wants to apply solid software engineering principles to build trusted, discoverable, and scalable data products - ultimately empowering every team across the organisation to make confident, data-driven decisions.

You’ll be working at the heart of a mission-driven company developing groundbreaking surgical robotics technology. Your work will help unlock innovation, improve data accessibility, and support teams working to bring life-changing medical technology to more patients.

Alongside impactful work, you’ll join a supportive and collaborative environment that values continuous learning, professional development, and technical excellence.

Key Responsibilities:

Playing a key role in shaping the foundations of a Databricks-based lakehouse platform - designing how the catalogue is structured, defining core dimensions/facts, and ensuring the platform is discoverable and useful across the business.
Writing clean, performant Python, SQL, and working confidently with Spark/PySpark.
Integrating third-party tools, connectors, and SaaS data sources into a cohesive data ecosystem.
Owning software components end-to-end: from idea, to build, to production (ensuring reliability and maintainability).
Championing continuous improvement and modern engineering practices.
Working closely with cross-functional stakeholders to turn real-world problems into elegant data solutions.
Producing clear, concise technical documentation.
Adapting within a fast-evolving environment and contributing across the data remit wherever needed.About You:

Have hands-on experience building Databricks lakehouse architectures and are excited by shaping foundational data infrastructure.
Understand how to engineer data platforms for trust, scalability, and discoverability, not just produce pipelines.
Are confident with Databricks, AWS, and the modern data stack.
Enjoy fast-paced, iterative delivery and creating user-friendly, value-driven outcomes.
Collaborate naturally, share ideas openly, and learn from those around you.
Are adaptable, curious, and motivated by continuous improvement and learning.
Bring strong experience in data engineering, particularly in greenfield or scaling environments (or equivalent).
Embrace “data as a product” thinking - ensuring datasets have clear purpose, documentation, quality checks, version control, and measurable value.
Think like a seasoned engineer: Git, CI, modular code, automated tests, alerting, and clean architecture are second nature.
Are excited to establish foundational patterns that others will follow.Why This Role Matters You’ll be joining a company that is building world-class medical technologies and breaking new ground in robotic surgery. The work is meaningful, the teams are supportive, and the opportunities for impact and growth are huge.

What are the benefits?:

Competitive basic salary
Medical cover 
Death in service
Additional Pension contribution
Keen to express your interest, or find out more?
Option 1: Click the apply button (don’t worry, we’ll discuss your CV before submitting)
Option 2: Call in to the SoCode Cambridge office and ask for Rachel
Option 3: Drop me a message on LinkedIn (Rachel Bush – SoCode Recruitment)

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.

Careers

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.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.