Lead Data Engineer

Lead Data Engineer

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Architect and own data pipelines, ensuring reliable and scalable data infrastructure for AI applications.
  • Company: Join a pioneering healthcare company transforming men's health and wellness.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Dynamic, fast-paced environment with a mission to revolutionise healthcare.
  • Why this job: Make a real impact in healthcare by leveraging AI to improve lives.
  • Qualifications: 5+ years in data engineering, strong AI/ML application experience, and advanced SQL skills.

The predicted salary is between 70000 - 90000 £ per year.

You will join our Data team as owner of our data infrastructure with an opportunity to architect and own the data pipelines, platforms and practices that will power our Data Platform. A key part of this role is improving and defining how stakeholders can use AI to self-serve their own analysis. You’ll sit at the intersection of data engineering and applied AI, working closely with analytics engineers and analysts. You will define the standards and systems that allow the data team and stakeholders to self-serve analysis using AI as a base— ensuring the data foundation is reliable, scalable and ready to fuel our AI and LLM capabilities.

What You’ll Do

  • Build and maintain scalable data pipelines to ingest, transform and integrate data from multiple sources, defining best practice along the way.
  • Implement robust monitoring for data ingestion jobs and take swift corrective action when issues arise.
  • Work with business stakeholders to translate requirements into efficient pipeline architectures, database structures and optimised data models.
  • Partner with analytics engineers to ensure clean, accessible data is available to analysts across the organisation.
  • Champion responsible AI principles in the design and deployment of data systems that underpin our LLM and RAG implementations.
  • Lead on development standards, version control, quality control, deployment and change management processes.
  • Monitor, measure and maintain high data quality standards across all data products and pipelines.

Who You Are

  • AI & LLM expertise: Experience building and deploying AI/ML-powered applications. A solid understanding of responsible AI principles and how they apply to data infrastructure and product development.
  • Data engineering foundation: 5+ years of commercial experience as a data engineer across multiple data products and pipelines. Advanced knowledge of GCP as a data warehouse. Advanced SQL skills with the ability to design and optimise complex queries at scale. Deep familiarity with modern analytics and data architectures, including data warehousing best practices. Experience with scalable backend systems and cloud platforms, with comfort across the full data engineering lifecycle — ingestion, cleaning, transformation and integration. Experience with dbt, Fivetran and Snowflake. Python proficiency. Previous experience in health, wellness, pharmaceutical or digital/e-commerce sectors.

How You Work

  • Customer-focused: you are genuinely excited about building products that drive positive change at scale.
  • Self-starter: you use your own initiative, anticipate problems before they arise and take full ownership from raw ingestion to final delivery.
  • Pragmatic problem-solver: you take genuine pleasure in finding the right solution and making sensible trade-offs under real-world constraints.
  • Growth mindset: you thrive in fast-paced scale-up environments and are energised, not unsettled, by ambiguity and pace.

Healthcare is broken. We’re fixing it — and we need your help. Back in 2019, we launched MANUAL to tackle men's health (starting with hair loss and sexual health). A few years later, we launched Voy with a focus on weight loss. But our ambition has always been bigger. Healthcare too often treats conditions in isolation, not people as a whole, and we're on a mission to prove there's a better way. In 2025, we evolved from MANUAL into Voy, a brand built for the long game: supporting people through every stage of life, not just a single diagnosis. Today, we support over 1 million members across the UK, Germany and Brazil, delivering personalised care across weight loss, menopause, hair loss and TRT (with more categories on the way). Ready to join us and change how healthcare feels for millions of people?

Lead Data Engineer employer: Voy

At Voy, we pride ourselves on being an exceptional employer that champions innovation and personal growth within the healthcare sector. Our collaborative work culture fosters creativity and empowers our employees to take ownership of their projects, particularly in the dynamic role of Lead Data Engineer, where you will directly influence how AI enhances our data infrastructure. With a commitment to professional development and a mission to revolutionise healthcare, we offer a unique opportunity to make a meaningful impact while enjoying a supportive environment that values your contributions.
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Contact Detail:

Voy Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Lead Data Engineer

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving AI and LLMs. This will give you an edge and demonstrate your hands-on experience to potential employers.

✨Tip Number 3

Prepare for interviews by brushing up on common data engineering scenarios and challenges. Be ready to discuss how you've tackled issues in the past, especially around building scalable data pipelines and ensuring data quality.

✨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 mission to revolutionise healthcare.

We think you need these skills to ace Lead Data Engineer

Data Pipeline Architecture
AI & LLM Expertise
Data Engineering
GCP (Google Cloud Platform)
SQL (Structured Query Language)
Data Warehousing Best Practices
Scalable Backend Systems
Cloud Platforms
Data Ingestion and Transformation
dbt (data build tool)
Fivetran
Snowflake
Python Proficiency
Problem-Solving Skills
Customer-Focused Mindset

Some tips for your application 🫡

Tailor Your CV: Make sure your CV speaks directly to the Lead Data Engineer role. Highlight your experience with data pipelines, AI, and any relevant projects that showcase your skills. We want to see how you can fit into our mission!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how your background aligns with our goals at StudySmarter. Be genuine and let your personality come through.

Showcase Your Technical Skills: Don’t hold back on your technical expertise! Make sure to detail your experience with GCP, SQL, and any tools like dbt or Fivetran. We’re looking for someone who can hit the ground running, so show us what you’ve got!

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 don’t miss out on any important updates. Plus, we love seeing applications come in through our own platform!

How to prepare for a job interview at Voy

✨Know Your Data Inside Out

Make sure you’re well-versed in the data engineering principles and practices mentioned in the job description. Brush up on your experience with GCP, SQL, and tools like dbt and Fivetran. Be ready to discuss specific projects where you’ve built scalable data pipelines or optimised data models.

✨Showcase Your AI Expertise

Since this role sits at the intersection of data engineering and applied AI, prepare to talk about your experience with AI/ML-powered applications. Highlight any projects where you’ve implemented responsible AI principles and how they influenced your data infrastructure decisions.

✨Prepare for Problem-Solving Scenarios

Expect to face real-world problem-solving questions during the interview. Think of examples where you’ve had to troubleshoot data ingestion issues or optimise a pipeline under tight deadlines. Show them your pragmatic approach to finding solutions and making trade-offs.

✨Understand the Company’s Mission

Familiarise yourself with the company’s journey and mission in healthcare. Be prepared to discuss how your skills can contribute to their goal of transforming healthcare. Showing genuine enthusiasm for their mission will set you apart from other candidates.

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