Senior Analytics Platform Engineer

Senior Analytics Platform Engineer

Full-Time 80000 - 80000 € / year (est.) Home office (partial)
Our Future Health

At a Glance

  • Tasks: Design and maintain analytics-ready data models to power scalable insights.
  • Company: Join Our Future Health, a mission-driven organisation transforming healthcare.
  • Benefits: Competitive salary, generous holiday, pension scheme, and wellbeing support.
  • Other info: Flexible working arrangements and a supportive, diverse workplace culture.
  • Why this job: Make a real impact on health outcomes for future generations.
  • Qualifications: Experience in analytics engineering, Python, and dbt expertise required.

The predicted salary is between 80000 - 80000 € per year.

We’re looking for a Senior Analytics Platform Engineer. In this role you will help shape the future of data at Our Future Health by building the foundations that power trusted, scalable analytics across the organisation. As a Senior Analytics Platform Engineer, you’ll design and maintain analytics‑ready data products that enable consistent, reliable insight at scale. You’ll work across the analytics platform, data product teams, and scientific users to improve how data is modelled, documented, and adopted, while also coaching others to build high‑quality analytical assets with confidence. This is a role where your impact multiplies, success means everyone can build better analytics, not just you. At Our Future Health, our mission is to transform the prevention, detection and treatment of conditions such as dementia, cancer, diabetes, heart disease and stroke. We’re looking for people to join us on our journey. If you’re looking for a new challenge where you can contribute to helping future generations live in good health for longer, then we’re keen to speak with you.

What you’ll be doing:

  • Designing and maintaining analytics‑ready data models in Snowflake using dbt, including data marts, metrics, and reusable analytical datasets.
  • Applying scalable modelling patterns and contributing to organisation‑wide standards and conventions.
  • Coaching analysts, data scientists, and science teams in analytics engineering best practice, modelling, testing, documentation, and data quality.
  • Enabling domain teams to own and maintain their data marts safely and confidently, with guidance and review to ensure alignment with platform standards.
  • Partnering with internal researchers to translate exploratory analysis into repeatable, well‑modelled datasets with clear definitions and reproducible insights.
  • Shaping analytical products around real use cases, ensuring data marts are intuitive, discoverable, and fit for purpose.
  • Owning data quality at the analytics layer, using dbt tests, monitoring, and close collaboration with platform engineers to resolve issues.
  • Building and maintaining the semantic layer in Snowflake and Omni to support consistent, self‑serve analytics.
  • Supporting adoption of Omni through documentation, examples, and hands‑on guidance.
  • Collaborating with data product teams on ingestion, data contracts, and quality expectations.
  • Working closely with Analytics Platform Engineers on dbt execution patterns, performance optimisation, and CI/CD improvements.
  • Mentoring mid‑level analytics engineers and contributing to a culture of high‑quality, scalable analytics.

What you won’t be doing:

  • Working in a siloed environment with no freedom to make decisions.
  • Working in a place where you can’t see the impact your expertise makes.

To succeed in this role you will be able to demonstrate some of the following skills and experience:

  • Proven analytics engineering experience with a track record of building analytics‑ready datasets.
  • Python engineering ability to produce clean, maintainable, production‑grade code.
  • Hands‑on dbt expertise including modelling, testing, documentation, and data quality.
  • Understanding of metrics and KPIs and how to translate them into well‑structured data models.
  • Experience working with analysts and data scientists to support and enable analytical work.
  • Clear, empathetic communication to explain modelling decisions to non‑engineers.
  • A coaching mindset that helps domain teams take ownership of their models.
  • Strong analytical problem‑solving with a focus on clarity, simplicity, and maintainability.
  • Comfort navigating complex data ecosystems and shaping standards across teams.
  • Interest in platform‑level concerns such as performance, orchestration, CI/CD, and reliability.
  • Experience with cloud‑native tooling including Kubernetes and containers.
  • Familiarity with semantic layers such as Snowflake, Omni, or Looker.
  • Experience in regulated or scientific environments where governance and reproducibility matter.

Salary: from £80,000 per annum.

Benefits:

  • Generous Pension Scheme – We invest in your future with employer contributions of up to 12%.
  • 30 Days Holiday + Bank Holidays – Enjoy a generous holiday allowance with the flexibility to take bank holidays when it suits you.
  • Enhanced Parental Leave – Supporting you during life’s biggest moments.
  • Cycle to Work Scheme – Save 25-39% on a new bike and accessories through salary sacrifice.
  • Home & Tech Savings – Get up to 8% off on IKEA and Currys products, spreading the cost over 12 months through salary sacrifice.
  • £1,000 Employee Referral Bonus – Know someone amazing? Get rewarded for bringing them on board!
  • Wellbeing Support – Access to Mental Health First Aiders, plus 24/7 online GP services and an Employee Assistance Programme for you and your family.
  • A Great Place to Work – We have a lovely Central London office in Holborn, and offer flexible and remote working arrangements.

Join us - let’s prevent disease together. At Our Future Health, we recognise the importance of having a diverse workforce and ensuring that all candidates, regardless of their background, have equitable access to our application process. We proactively encourage applicants who identify as having a disability, neurodiversity, or long‑term health conditions to let us know if they require any reasonable adjustments as part of their application process. If you do require any reasonable adjustments, please email us at talent@ourfuturehealth.org.uk.

Senior Analytics Platform Engineer employer: Our Future Health

At Our Future Health, we pride ourselves on being an exceptional employer dedicated to transforming healthcare through data-driven insights. Our collaborative work culture fosters innovation and personal growth, offering extensive training and mentorship opportunities for our employees. With a generous benefits package, including a robust pension scheme, flexible working arrangements, and a supportive environment in our vibrant Central London office, we empower our team to make a meaningful impact on future generations' health.

Our Future Health

Contact Detail:

Our Future Health Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Analytics Platform Engineer

Tip Number 1

Network like a pro! Reach out to folks in the analytics community, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Show off your skills! Create a portfolio showcasing your analytics projects, especially those involving dbt and Snowflake. This gives potential employers a taste of what you can do and sets you apart from the crowd.

Tip Number 3

Prepare for interviews by brushing up on common analytics engineering questions. Be ready to discuss your experience with data modelling, coaching teams, and ensuring data quality. Practice makes perfect!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who want to make a difference in health analytics.

We think you need these skills to ace Senior Analytics Platform Engineer

Analytics Engineering
Snowflake
dbt
Python
Data Modelling
Data Quality Assurance
KPI Understanding

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with analytics engineering, dbt, and Python. We want to see how your skills align with the role of Senior Analytics Platform Engineer!

Showcase Your Impact:When detailing your past experiences, focus on the impact you've made in previous roles. We love to see how you've contributed to building analytics-ready datasets and improved data quality.

Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to explain your technical skills and experiences, especially when discussing complex data ecosystems. We appreciate clarity!

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape the future of data at Our Future Health.

How to prepare for a job interview at Our Future Health

Know Your Data Models

Before the interview, brush up on your knowledge of analytics-ready data models, especially in Snowflake and dbt. Be prepared to discuss how you've designed and maintained these models in previous roles, as well as any challenges you faced and how you overcame them.

Showcase Your Coaching Skills

Since this role involves mentoring others, think of specific examples where you've coached analysts or data scientists. Highlight how you helped them understand best practices in analytics engineering and how you fostered a culture of high-quality analytics.

Communicate Clearly and Empathetically

Practice explaining complex modelling decisions in simple terms. The interviewers will want to see that you can communicate effectively with non-engineers. Prepare to share instances where your clear communication made a difference in a project.

Demonstrate Problem-Solving Abilities

Be ready to tackle some analytical problem-solving questions during the interview. Think about how you've approached complex data issues in the past, focusing on clarity, simplicity, and maintainability in your solutions.