At a Glance
- Tasks: Build data models and pipelines to empower analysts with clean, reliable data.
- Company: Join the UK's leading premium publisher with iconic media brands.
- Benefits: Enjoy health perks, flexible work options, and exclusive discounts.
- Other info: Collaborative culture focused on creativity and diversity.
- Why this job: Make a real impact by transforming data into insights for top brands.
- Qualifications: 2-4 years in data engineering, proficient in SQL and Python.
The predicted salary is between 36000 - 60000 £ per year.
We’re the UK’s leading premium publisher, and the people behind iconic media brands such as Cosmopolitan, Esquire, ELLE, Harper’s Bazaar and Country Living. We’ve created a working environment that encourages everyone to pull together. We never stop looking for brave new ideas. We’ll always try to develop and improve, we trust each other to do our best, and we have fun as we build on our heritage to make history.
Please note: This role is office based 4 days a week.
As the Analytics Engineer you will play a key role in helping the business understand our customers. Sitting between data engineering and analytics, you’ll be the person who empowers analysts with clean, reliable, and accessible data, building the datasets, pipelines, and tools they need to explore insights, while also enabling and contributing to more advanced analytics such as RFM scoring, segmentation, and predictive modelling.
Main Duties
- Build and maintain data models and pipelines within our GCP data environment to make data accessible, reliable, and usable for analysts and stakeholders.
- Collaborate with Merkle engineers (who maintain our GCP-based data lake) to ensure data lake architecture supports evolving analytical and reporting needs.
- Work with analysts to understand their data requirements, designing scalable solutions that support dashboards, customer metrics, and campaign analytics.
- Support advanced analytics projects, including RFM scoring, customer segmentation, and predictive models that help inform marketing and retention strategies.
- Optimise data workflows to improve performance, reduce duplication, and support self‑serve analytics through tools like Looker and our CDP, ActionIQ.
What We Are Looking For
- At least 2–4 years of experience in a data or analytics engineering role.
- Proficient in SQL and experienced working with large datasets within GCP (BigQuery) or similar cloud environments.
- Experience with Python for data transformation and automation.
- Experience with code management, review and reversion using GitHub.
- Comfortable collaborating with both analysts and engineers, translating business needs into robust technical solutions.
- Familiarity with Looker (or another BI tool) and an understanding of how to structure data for efficient dashboarding and self‑serve analytics.
- Exposure to customer analytics concepts such as segmentation, LTV, churn, and RFM analysis is a plus.
- An interest in predictive analytics or data science (experience in predictive modelling or machine learning would be a bonus).
- Strong communicator who enjoys helping others make the most of data.
Benefits
Your benefits at Hearst UK are more than just extras—they are tools to help you thrive in every part of life.
- Hearst Exclusives – Only for You! Get adventurous with Good Housekeeping Taste and Beauty Testing Panels – yes, you could be trying the next big thing in beauty, food & drink. Snag luxe beauty steals at our legendary office sample sales – score big on top brands without breaking the bank!
- Inclusion, Health & Wellbeing: Feel Your Best Stay healthy with Specsavers eye care, a company‑funded Health Cash Plan, and access to mental health support. Get active and stress‑free with discounted gym memberships and the Cycle to Work scheme. Embrace flexibility with a Location Flex and Holiday Exchange to take time when you need it. Take time to give back with a Charity Day and access wellbeing resources whenever you need them. Join one of our Hearst ERG Groups.
- Financial Wellness – Boost Your Budget Plan ahead with a generous Workplace Pension, Income Protection, Life Assurance and Season Ticket Loan for easier commuting. Make smarter money moves using Salary Finance tools, Financial Wellbeing sessions, and Home Tech benefits to spread costs. Treat yourself with major discounts across London plus everyday savings via the HAPI at Hearst app.
Hearst UK is deeply committed to using our influential brands to reflect the world we want to live in – one that respects, protects, represents and uplifts the voices and opinions of all people. As a business, we recognise the significant benefits of creativity, collaboration and innovation that comes with diverse teams. Not only is diversifying the voices in our organization the right thing to do, but it also helps us to make powerful and exciting content that can be enjoyed by many more people. This is why we’re working to build a sense of true belonging within our business and foster a culture in which everyone feels heard.
Analytics Engineer employer: Hearst UK
At Hearst UK, we pride ourselves on being a leading premium publisher that fosters a collaborative and innovative work culture. As an Analytics Engineer, you'll benefit from a supportive environment that encourages personal growth and creativity, alongside comprehensive health and wellbeing initiatives, flexible working options, and unique perks like exclusive product testing and discounts. Join us in shaping the future of media while enjoying a fulfilling career in a vibrant London setting.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. Ask them about their experiences and the company culture; it’s a great way to get insider info and make a memorable impression.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and Python skills. Be ready to discuss how you’ve used these tools in past projects, especially in relation to data pipelines and analytics. Show us you can walk the talk!
✨Tip Number 3
Don’t just focus on technical skills; highlight your communication abilities too. We want to see how you can translate complex data into actionable insights for analysts and stakeholders. Share examples of how you’ve done this before!
✨Tip Number 4
Finally, 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 team and contributing to our exciting projects.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Analytics Engineer role. Highlight your experience with SQL, GCP, and any relevant projects that showcase your skills in data modelling and analytics. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data and how your background aligns with our mission at Hearst UK. Don’t forget to mention any specific projects or experiences that relate to the job description.
Showcase Your Collaboration Skills:Since this role involves working closely with analysts and engineers, make sure to highlight your teamwork experience. Share examples of how you've successfully collaborated on projects in the past, as we value a collaborative spirit here at StudySmarter.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Hearst UK
✨Know Your Data Tools
Make sure you brush up on your SQL skills and get familiar with GCP, especially BigQuery. Be ready to discuss how you've used these tools in past projects, as well as any experience you have with Python for data transformation.
✨Understand the Business Needs
Before the interview, take some time to research the company’s brands and their target audience. Think about how your role as an Analytics Engineer can help them understand their customers better and be prepared to share ideas on how you would approach this.
✨Showcase Collaboration Skills
This role involves working closely with both analysts and engineers. Be ready to provide examples of how you've successfully collaborated in the past, translating business needs into technical solutions. Highlight any experience you have with GitHub for code management too!
✨Prepare for Advanced Analytics Discussions
Since the role supports advanced analytics projects, brush up on concepts like RFM scoring and customer segmentation. Be prepared to discuss any relevant experience you have and how you can contribute to predictive modelling efforts.