At a Glance
- Tasks: Lead the development of high-quality analytics data models and mentor a growing team.
- Company: Join a mission-driven health research programme transforming lives through data.
- Benefits: Competitive salary, generous pension, 30 days holiday, and enhanced parental leave.
- Other info: Flexible hybrid working with opportunities for professional growth and influence.
- Why this job: Make a real impact on health outcomes while shaping the future of analytics engineering.
- Qualifications: Experience in analytics engineering, strong SQL skills, and leadership abilities.
The predicted salary is between 80000 - 80000 ÂŁ per year.
Our Future Health is an ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation of new diagnostic tools, to help identify and treat diseases early, when outcomes are usually better. With over 2.5M volunteers across the UK, we’re now the world’s biggest health research programme of its kind, and our volunteer group is also more diverse than other, similar health research programmes. Technology and data are central to our mission. Our systems power web sites, clinics across the UK, secure analytics and research systems, pipelines that process highly sensitive health and genetic data, and we are continuing to grow our engineering capability to support this ambition.
We’re now growing our analytics engineering capability, recognising it as critical to unlocking the value of our data. This is a chance to join early, shape the function, and work on genuinely unique health data challenges. The Senior Analytics Engineer plays a strategic and technical leadership role in enabling high quality, consistent, and scalable analytics across the organisation. This role not only delivers trusted data models but also sets standards, drives best practices, and shapes the direction of analytics engineering. By leading on modelling approaches, mentoring analysts and data scientists, and partnering with stakeholders across the organisation, the role amplifies impact at scale, ensuring analytics is robust, reusable, and aligned to strategic priorities. This role is critical in advancing the organisation's analytics maturity and building a future‑ready data platform.
Why join?
- Work with large‑scale, real‑world health data
- Build trusted, reusable data products used across science and business
- Help develop data quality, testing, and observability from the ground up
- Enable self‑serve and AI‑powered analytics for non‑technical users
- Join at an early stage of team growth with real influence; you’ll lead initiatives and work directly with stakeholders
- Mission‑led: your work contributes to improving health outcomes at scale
You will:
- Lead development of high‑quality analytics data models
- Architect and build scalable, well‑governed dbt models in Snowflake, including data marts, metrics, and reusable datasets.
- Define and evolve modelling standards, conventions, and best practices across the organisation.
- Review and guide implementation of models to ensure consistency, scalability, and performance.
- Set standards and enable teams
- Act as a technical leader and mentor for analytics engineers, analysts, and data scientists.
- Establish best practices for modelling, testing, documentation, and data quality.
- Enable domain teams to safely own and extend their data models within a governed framework.
- Strategic partnership with business and science teams
- Translate complex analytical and research problems into scalable, production‑grade data models.
- Shape how metrics and datasets are defined and used across the organisation.
- Influence stakeholders on best practices in data usage, reproducibility, and analytical design.
- Improve data quality, documentation, and reproducibility in workflows.
- Own data quality and reliability frameworks
- Design and implement robust testing, monitoring, and alerting frameworks for analytics data.
- Define SLAs and data quality standards in collaboration with platform and data engineering teams.
- Lead root‑cause analysis and resolution of data quality issues.
- Drive self‑serve analytics at scale
- Own and evolve semantic layers in Snowflake and BI tools (e.g., Omni).
- Define governed approaches to metrics and self‑serve analytics.
- Champion adoption through clear documentation, training, and enablement strategies.
- Contribute to and shape the Analytics Platform
- Partner with platform engineers on architecture, performance optimisation, and orchestration.
- Drive improvements in analytics CI/CD, deployment workflows, and developer experience.
- Influence data contracts, ingestion patterns, and overall platform design.
We’re London‑based (Holborn) and work on a flexible hybrid basis (typically weekly with a team day every 2 weeks). We’d like to prioritise candidates who can reasonably commute and benefit from in‑person collaboration.
Requirements
We welcome applications from all who may not feel they match the full criteria, so if you have most of the below, we’d like to hear from you:
Essential:
- Significant experience in analytics engineering or a closely related field, including experience operating at a senior level.
- Strong business and strategic acumen; able to shape metrics, data models, and analytical approaches.
- Deep expertise in SQL and advanced analytics data modelling.
- Strong experience with dbt in production environments, including project structuring and best practices.
- Experience working with modern data warehouses (e.g., Snowflake, Google Big Query) at scale.
- Proficiency in Python for data workflows, automation, or tooling.
- Proven experience defining and implementing data quality, testing, and governance frameworks.
- Experience mentoring others and providing technical leadership.
- Strong stakeholder management and communication skills, with the ability to influence decision‑making.
Bonus / Desirable
- Experience designing and scaling semantic layers and metrics frameworks.
- Exposure to product analytics tools (e.g., Mixpanel, Amplitude).
- Experience contributing to platform‑level decisions (e.g., orchestration, CI/CD, performance tuning).
- Experience working in federated or domain‑oriented data ownership models (e.g., data mesh).
Benefits
- Competitive base salary from ÂŁ80,000
- Generous Pension Scheme – We invest in your future with employer contributions of up to 12%
- 30 Days Holiday pro‑rate + 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
Senior Analytics Engineer employer: Our Future Health UK
Contact Detail:
Our Future Health UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to people 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 analytics projects, data models, and any cool stuff you've built. This is your chance to demonstrate your expertise and make a lasting impression on hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company's mission. Be ready to discuss how your experience aligns with their goals, especially around health data and analytics engineering.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of our mission to improve health outcomes.
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in analytics engineering. We want to see how your skills align with our mission and the specific requirements of the Senior Analytics Engineer role.
Showcase Your Technical Skills: Don’t hold back on showcasing your SQL, dbt, and Python expertise! We’re looking for someone who can hit the ground running, so make sure to include relevant projects or experiences that demonstrate your technical prowess.
Highlight Your Leadership Experience: As a Senior Analytics Engineer, you’ll be mentoring others and leading initiatives. Share examples of how you’ve successfully guided teams or influenced stakeholders in your previous roles. We love seeing candidates who can inspire and drive change!
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 this exciting opportunity. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Our Future Health UK
✨Know Your Data Models
Make sure you’re well-versed in analytics data modelling, especially with dbt and Snowflake. Be ready to discuss your past experiences in building scalable models and how you’ve ensured data quality and governance.
✨Showcase Your Leadership Skills
As a Senior Analytics Engineer, you’ll be expected to mentor others. Prepare examples of how you’ve led teams or projects in the past, focusing on how you’ve influenced best practices and improved analytics maturity.
✨Understand the Business Impact
Familiarise yourself with how analytics can drive health outcomes. Be prepared to discuss how your work can contribute to the organisation’s mission and how you’ve translated complex problems into actionable insights in previous roles.
✨Prepare for Stakeholder Engagement
You’ll need strong communication skills to influence stakeholders. Think of examples where you’ve successfully managed stakeholder expectations or collaborated with cross-functional teams to achieve a common goal.