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For Companies At a Glance
- Tasks: Lead data initiatives, turning complex data into actionable insights for smarter decisions.
- Company: Join a fast-growing, mission-driven tech team with a collaborative culture.
- Benefits: Competitive salary, personal development budget, private health insurance, and flexible remote work.
- Why this job: Own the analytics function and influence business strategy in a global tech company.
- Qualifications: Strong SQL, data visualisation skills, and experience leading analytics initiatives.
- Other info: Unique opportunity to mentor and champion a data-driven culture.
The predicted salary is between 80000 - 90000 £ per year.
We are currently looking for a Lead Data Analyst to join our client's fast-growing, collaborative, and mission-driven tech team. In this role, you'll take ownership of their end‐to‐end analytics strategy, turning complex data into actionable insights that fuel smarter decisions across product, marketing, and business operations. You will lead initiatives that shape how data informs strategy, helping the business scale intelligently while continuing to innovate.
As a Lead Data Analyst, you'll design scalable data models, streamline pipelines, and empower teams with clear, visual insights. You'll play a key role in defining what success looks like, ensuring the data tells a story that drives growth, product adoption, and customer engagement.
The Opportunity
As the Lead Data Analyst, you'll take the lead on:
- Designing and implementing a data strategy that enables business‐wide visibility.
- Building and optimising data pipelines, models, and dashboards.
- Leading data storytelling, translating insights into actionable outcomes.
- Partnering with Product, Engineering, and Growth teams to define key metrics.
- Championing a data‐driven culture and mentoring analysts or engineers as needed.
- Leveraging product and user data to guide decision‐making and experimentation.
This is a unique opportunity to own the analytics function within a global, remote‐first tech company, working at scale and influencing both business strategy and user experience.
What's in it for you?
- Competitive salary (depending on location & experience)
- £2,500 annual personal development budget
- Private health insurance (country dependent)
- Fully remote, flexible working
- Enhanced parental leave
- Equipment & home office support
Skills and Experience
Must Have:
- Strong SQL and data modelling experience
- Advanced data visualisation skills (Tableau, Power BI or similar)
- Experience leading analytics or data initiatives end‐to‐end
- Proficiency in Python or similar for data manipulation
- Excellent communication and stakeholder management skills
Nice to Have:
- Experience with dbt or modern data stack tools
- Understanding of experimentation / A/B testing frameworks
- Familiarity with event‐based data and product analytics
- Exposure to SaaS, cybersecurity, or e‐learning environments
If you'd like to be considered for the Lead Data Analyst position and feel you'd be an ideal fit for our client's innovative and collaborative team, please send your CV by clicking the Apply button below.
Lead Data Analyst in London employer: Data Science Festival
Contact Detail:
Data Science Festival Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Analyst in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your data visualisation and analytics prowess. It’s a great way to demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data analysis. We recommend using the STAR method to structure your answers – it’ll help you shine!
✨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 seeing candidates who take that extra step!
We think you need these skills to ace Lead Data Analyst in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences mentioned in the job description. Highlight your SQL, data visualisation, and leadership experience to show us you're the perfect fit for the Lead Data Analyst role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data and how you can contribute to our mission-driven tech team. Share specific examples of how you've turned complex data into actionable insights in previous roles.
Showcase Your Data Storytelling Skills: In your application, emphasise your ability to translate data into clear, visual insights. We want to see how you've led data initiatives and partnered with teams to drive growth and engagement through effective storytelling.
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 lead our analytics function.
How to prepare for a job interview at Data Science Festival
✨Know Your Data Tools
Make sure you’re well-versed in SQL and data visualisation tools like Tableau or Power BI. Be ready to discuss specific projects where you've used these tools to turn complex data into actionable insights.
✨Showcase Your Leadership Skills
As a Lead Data Analyst, you'll be expected to lead initiatives. Prepare examples of how you've successfully led analytics projects or mentored team members, highlighting your ability to drive a data-driven culture.
✨Master the Art of Data Storytelling
Practice explaining how you've translated data insights into actionable outcomes in previous roles. Use clear, concise language to demonstrate your ability to communicate complex information effectively.
✨Understand the Business Context
Familiarise yourself with the company’s mission and how data informs their strategy. Be prepared to discuss how you can leverage product and user data to guide decision-making and experimentation in their specific context.
