At a Glance
- Tasks: Analyse data to uncover insights and optimise marketing performance.
- Company: Join a well-known consumer brand on a mission to understand customers better.
- Benefits: Competitive pay, flexible work environment, and opportunities for growth.
- Other info: Fast-paced environment with a focus on collaboration and innovation.
- Why this job: Make a real impact by driving customer acquisition and retention through data.
- Qualifications: Strong SQL and Python skills, with experience in marketing analytics.
The predicted salary is between 36000 - 60000 £ per year.
We’re partnering with a well‑known consumer brand that’s on a mission to deepen its understanding of customer behaviour and optimise marketing performance. They’re scaling fast and are looking for a Marketing Data Analyst to help the team better understand customer behaviour and optimise acquisition performance across digital channels.
This is a great opportunity for someone who enjoys working in fast‑paced, data‑driven environments and partnering directly with marketing leaders to drive commercial impact.
The Project:
- Partner closely with the Marketing and Growth teams to tackle complex commercial challenges that drive customer acquisition and retention.
- Analyse customer and campaign data to uncover actionable insights and growth opportunities.
- Build and maintain Looker dashboards to enable data‑led decision‑making.
- Conduct deep dives into channel performance, customer LTV, CAC, and ROAS to guide spend and strategy.
- Work with marketing data sources (CRM, referral, and paid media) to evaluate performance and efficiency.
What we’re looking for:
- Strong SQL and Python (or R) skills for hands‑on analysis.
- Proven experience supporting Marketing, Growth, or Performance teams in a data‑focused capacity.
- Expertise in Looker and BigQuery (essential).
- Deep understanding of marketing metrics such as CAC, LTV, Payback Period, and ROAS.
- Experience working in a high‑growth, fast‑moving environment.
- Strong commercial mindset and ability to translate data into clear business recommendations.
You must be based in the UK. Unfortunately this role does not offer sponsorship.
Seniority level: Mid‑Senior level
Employment type: Contract
Job function: Analyst
Industry: Data Infrastructure and Analytics
Marketing Data Analyst in England employer: Cognify Search
Cognify Search offers an exceptional work environment for the Head of ML & AI, where innovation meets collaboration. With a focus on enhancing customer experience through cutting-edge technology, employees benefit from a culture that prioritises professional growth and teamwork. Located in a dynamic eCommerce hub, this role provides unique opportunities to lead impactful projects while working alongside industry experts.
StudySmarter Expert Advice🤫
We think this is how you could land Marketing Data Analyst in England
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at companies you're interested in. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your SQL, Python, or Looker expertise. This not only demonstrates your capabilities but also gives you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for the interview by diving deep into the company’s marketing strategies. Understand their customer acquisition metrics and think about how you can contribute. Tailoring your insights to their specific challenges can really 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. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Marketing Data Analyst in England
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Marketing Data Analyst. Highlight your SQL and Python skills, and any experience you have with Looker and BigQuery. We want to see how your background aligns with our mission!
Showcase Your Analytical Skills:In your application, don’t just list your skills—show us how you've used them! Share specific examples of how you've analysed data to drive marketing decisions or improve performance. We love seeing real-world applications!
Be Clear and Concise:When writing your cover letter, keep it straightforward. We appreciate clarity, so get to the point about why you're a great fit for this fast-paced environment. Make it easy for us to see your potential impact!
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 you’re keen on joining our team!
How to prepare for a job interview at Cognify Search
✨Know Your Data Inside Out
Make sure you brush up on your SQL and Python (or R) skills before the interview. Be ready to discuss how you've used these tools in past roles, especially in relation to marketing metrics like CAC and LTV. The more specific examples you can provide, the better!
✨Familiarise Yourself with Looker and BigQuery
Since expertise in Looker and BigQuery is essential for this role, take some time to explore these platforms. If possible, create a sample dashboard or two to showcase your skills. This will not only impress your interviewers but also give you practical insights to discuss.
✨Understand the Company’s Marketing Goals
Research the consumer brand you're interviewing with. Understand their current marketing strategies and challenges. This will help you tailor your answers to show how you can directly contribute to their goals, especially in customer acquisition and retention.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve hypothetical problems related to marketing data analysis. Practice articulating your thought process clearly and logically. Use the STAR method (Situation, Task, Action, Result) to structure your responses effectively.
