At a Glance
- Tasks: Design and maintain data pipelines for healthcare AI, ensuring data quality and reliability.
- Company: Join a pioneering team reshaping the healthcare industry with innovative technology.
- Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team where your contributions truly matter.
- Why this job: Make a real impact in healthcare by building cutting-edge data solutions.
- Qualifications: 7+ years in data engineering, proficient in Python, and experienced with large datasets.
The predicted salary is between 48000 - 72000 £ per year.
Location: UK or Europe | Remote (±2–3 hrs GMT overlap mandatory)
Reports to: Head of Engineering
Existing Clients: Top 100 Lifesciences, MedTech and Pharma companies
Type: Full-time
Core responsibilities & objectives
- Design, build, and maintain batch/streaming data pipelines, ingestion, cleaning, normalisation, enrichment, deduplication.
- Build and own ML/LLM pipelines end-to-end: document parsing, chunking, embeddings generation, vector indexing, agentic tool calling, multi-step workflows, retries, fallbacks, and state handling.
- Write production-grade, well-tested Python that processes large volumes of data and documents reliably.
- Own pipeline health: if data is stale, broken, or wrong, it's on you.
- Work autonomously to project deadlines with minimal hand-holding.
Key qualifications & skills (non-negotiable)
- 7+ years in backend data-heavy development or data engineering.
- Highly proficient in Python.
- Hands-on experience with large datasets and high-velocity data streams (Kafka, Flink, Spark).
- Strong with pipeline orchestration tools (Airflow, MLflow, or equivalent).
- Solid SQL skills (Postgres, BigQuery, or Snowflake) and NoSQL experience (DynamoDB, OpenSearch, Elastic).
- Real experience with LLM workflows: RAG architectures, embeddings/vector DBs, prompt engineering, function/tool calling, observability.
- Deep understanding of ETL/ELT patterns and data processing at scale.
Preferred background (strong signals)
- Experience with AWS data stack at scale.
- Exposure to healthcare, life sciences, or regulated industries.
- Built and shipped data, ML and LLM-powered pipelines in production.
- Has debugged a pipeline and knows why observability matters.
- Worked in a fast-moving startup where "that's not my job" doesn't exist.
What will get you rejected
- "I set up the pipeline, someone else monitors it" mindset.
- Tutorials and side projects but no production experience at scale.
- Can't explain trade-offs between streaming vs. batch, or why you chose one vector DB over another.
- Needs detailed specs before writing a line of code.
- No curiosity about healthcare or what the data actually means.
Interested? We're a distributed team solving hard problems that will reshape the healthcare industry for a generation. If you want ownership, not just tickets, we'd like to hear from you.
Senior Data Engineer – Healthcare AI employer: Vamstar
As a Senior Data Engineer in our innovative healthcare AI team, you'll join a dynamic and remote-first environment that prioritises autonomy and ownership over your work. We offer competitive benefits, a collaborative culture that encourages continuous learning, and the opportunity to make a significant impact on the healthcare industry by working with top-tier clients. With a focus on employee growth and a commitment to solving complex challenges, this role is perfect for those looking to advance their careers while contributing to meaningful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer – Healthcare AI
✨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 Vamstar!
✨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 – Healthcare AI at Vamstar.
✨Leverage Professional Networks
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 Vamstar.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer – Healthcare AI at Vamstar, 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 – Healthcare AI
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 Vamstar, 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 Vamstar. 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 Vamstar
✨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 Vamstar!
✨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.
