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- Tasks: Build and maintain a marketing database for personalised consumer experiences.
- Company: Join a global lifestyle brand with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for growth.
- Why this job: Lead data initiatives that shape consumer insights and drive brand success.
- Qualifications: Experience with data tools, Python, SQL, and cloud platforms.
- Other info: Collaborative team environment with a focus on creativity and impact.
The predicted salary is between 36000 - 60000 £ per year.
A global lifestyle brand is hiring a Data Engineer to build and maintain a marketing database that supports scalable analytics and personalised consumer experiences. The role sits within the Consumer Intelligence and Experience (CIX) team, which leads market research, segmentation, and activation across all brands and channels. You will be the lead developer responsible for enabling clean, structured data across the organisation.
Responsibilities:
- Design and maintain scalable data pipelines and architectures
- Ensure data quality, security, and governance across systems
- Collaborate with data scientists, analysts, and product teams
- Oversee data collection, transformation, and validation
- Use Python, SQL, and Excel to process and model data
Requirements:
- Experience with media data ELT tools and marketing APIs
- Familiarity with marketing datamarts and performance metrics
- Cloud experience with AWS, GCP, or Snowflake
- Proficiency in Python, SQL, Git, and DBT
- Knowledge of MMM/MTA and deployment tools like Airflow or Docker
Data Engineer - Retail and Luxury in London employer: FreshMinds Talent
Contact Detail:
FreshMinds Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Retail and Luxury in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in data roles. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and data pipelines. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing data architectures or solving data quality issues.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Data Engineer - Retail and Luxury in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and any relevant cloud platforms like AWS or GCP. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've designed data pipelines or worked with marketing data. This gives us a clear picture of your hands-on experience and how you can contribute to our team.
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. Explain why you're excited about the role and how your background fits with our mission at StudySmarter. We love enthusiasm!
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 the role. We can't wait to hear from you!
How to prepare for a job interview at FreshMinds Talent
✨Know Your Data Tools
Make sure you brush up on your knowledge of Python, SQL, and any ELT tools you've used. Be ready to discuss how you've applied these in past projects, especially in relation to marketing data and performance metrics.
✨Showcase Your Collaboration Skills
Since this role involves working with data scientists, analysts, and product teams, prepare examples of how you've successfully collaborated in the past. Highlight any specific projects where teamwork led to improved data quality or insights.
✨Understand the Business Context
Familiarise yourself with the retail and luxury sectors. Research the company’s brands and their marketing strategies. This will help you demonstrate how your data engineering skills can directly support their consumer intelligence goals.
✨Prepare for Technical Questions
Expect to face technical questions about data pipelines, governance, and cloud platforms like AWS or GCP. Practice explaining complex concepts in simple terms, as you may need to communicate these ideas to non-technical stakeholders.
