Senior Analytics Engineer in London

Senior Analytics Engineer in London

London Full-Time 60000 - 80000 € / year (est.) No home office possible
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At a Glance

  • Tasks: Transform raw data into impactful insights for AI products and business decisions.
  • Company: Fast-growing healthcare scale-up focused on data-driven solutions.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and patient outcomes.
  • Why this job: Shape the future of healthcare with your data expertise and make a real difference.
  • Qualifications: 3+ years in analytics engineering, advanced SQL skills, and experience with AI/ML workflows.

The predicted salary is between 60000 - 80000 € per year.

You will join our Data team as a senior analytics engineer modelling raw data and turning it into production ready tables for stakeholders and AI products that underpin the decisions that shape our business. This is a high‐impact role at the heart of a fast‐growing healthcare scale‐up — one where the data you model and the standards you set will directly influence how every team in the company operates, and how well our AI‐powered products perform.

You'll work closely with data and business stakeholders. You will be the bridge between raw data and meaningful insight, ensuring our modern data stack — built on BigQuery, dbt and Looker — is scalable, trusted and AI‐ready. Your work will underpin both the analytical decisions of our internal teams and the performance of the patient‐facing AI tools we build. You'll have genuine ownership over the data models and governance practices that underpin our data function. At a company growing as fast as ours, the standards you establish today will shape how we scale tomorrow — across products, markets and millions of patient interactions.

What You'll Do

  • Architect, model and optimise the core data models that power analytics and AI applications across the business, building for scale and performance from the ground up.
  • Ensure the data layer is structured to support AI and LLM use cases — including feature pipelines, evaluation datasets and the clean, well‐documented data that reliable AI products depend on.
  • Partner with cross‐functional teams across marketing, finance, operations and product to translate business requirements into robust, reliable technical solutions.
  • Own data governance of the data models you own — ensuring integrity, consistency and security while maintaining documentation and enforcing best practices.
  • Shape our data culture, driving adoption of rigorous modeling frameworks and analytical standards.
  • Identify opportunities to improve the performance, reliability and usability of our data stack, and take full ownership of seeing those improvements through.

Who You Are

  • AI & LLM awareness priority: A working understanding of how AI and LLM‐powered products consume data — including familiarity with feature engineering, evaluation pipelines and the data quality standards these systems require.
  • Experience contributing to or supporting AI/ML workflows, whether through building feature stores, curating training data, or structuring outputs for model consumption.
  • Technical expertise: 3+ years of experience in analytics engineering, data engineering or a closely related role. Advanced SQL skills — you can design, optimise and debug complex queries with confidence. Hands‐on experience with dbt or Dataform, and a strong track record of building scalable, well‐structured data models. Comfortable working within a modern data stack; direct experience with BigQuery and Looker is a strong advantage.
  • Analytical acumen: Strong understanding of measurement approaches, data analysis and statistics — you think carefully about what a metric actually means before you build it. Able to hold both the technical and business context simultaneously, ensuring every data solution is anchored to a real company objective. Experienced in data governance, quality assurance and documentation — you understand that trusted data is the product.

How You Work

  • A natural collaborator who can earn the trust of both data analysts and non‐technical stakeholders alike.
  • Takes ownership end‐to‐end — from understanding a business problem to delivering a solution the whole company can rely on.
  • Excited by the challenge of building in a fast‐paced environment and motivated by the idea that your work helps improve patient outcomes at scale.
  • Someone who resonates with ownership, strategic thinking and the pace of a high‐growth scale‐up.

Senior Analytics Engineer in London employer: Voy

Join our dynamic healthcare scale-up as a Senior Analytics Engineer, where your expertise will directly impact patient outcomes and drive the success of our AI-powered products. We foster a collaborative work culture that values innovation and ownership, providing ample opportunities for professional growth in a fast-paced environment. With a modern data stack and a commitment to excellence, you'll play a crucial role in shaping our data practices and influencing every aspect of our business.

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Contact Detail:

Voy Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Analytics Engineer in London

Tip Number 1

Network like a pro! Reach out to people in the industry, especially those already working at companies you're interested in. A friendly chat can open doors and give you insider info that could help you stand out.

Tip Number 2

Show off your skills! If you’ve got a portfolio or examples of your work, make sure to share them during interviews. This is your chance to demonstrate how you can turn raw data into actionable insights.

Tip Number 3

Prepare for the technical stuff! Brush up on your SQL and any tools mentioned in the job description, like BigQuery or dbt. Being able to talk confidently about your experience with these will definitely impress the hiring team.

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, it shows you’re genuinely interested in joining our awesome team!

We think you need these skills to ace Senior Analytics Engineer in London

Data Modelling
BigQuery
dbt
Looker
SQL
Data Governance
Feature Engineering

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Analytics Engineer role. Highlight your experience with SQL, dbt, and any AI/ML projects you've worked on. We want to see how you can contribute to our data team!

Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data and how your background makes you a great fit for this role. Share specific examples of how you've tackled challenges in analytics engineering before. This is your chance to shine!

Showcase Your Projects:If you've worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to mention them. We love seeing real-world applications of your skills, especially those that demonstrate your understanding of data governance and AI.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our fast-growing team!

How to prepare for a job interview at Voy

Know Your Data Stack

Familiarise yourself with the modern data stack mentioned in the job description, especially BigQuery, dbt, and Looker. Be ready to discuss how you've used these tools in your previous roles and how they can be leveraged to improve data models and governance.

Showcase Your Analytical Skills

Prepare to demonstrate your analytical acumen by discussing specific metrics you've built or optimised in the past. Think about how you can explain the importance of these metrics in a business context, showing that you understand both the technical and business sides of analytics.

Emphasise Collaboration

Since this role involves working closely with cross-functional teams, be prepared to share examples of how you've successfully collaborated with non-technical stakeholders. Highlight your ability to translate complex data concepts into understandable insights for different audiences.

Ownership and Governance Mindset

Express your understanding of data governance and quality assurance. Share experiences where you've taken ownership of data models and ensured their integrity and security. This will show that you resonate with the company's emphasis on building a trusted data culture.