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- Tasks: Design and maintain databases to support marketing analytics in a luxury retail environment.
- Company: Join a leading client in the luxury lifestyle and retail industry.
- Benefits: Competitive day rate, hybrid work model, and opportunity for professional growth.
- Other info: Collaborate with data scientists and work in a dynamic, supportive team.
- Why this job: Make an impact on marketing strategies with high-quality data and innovative analytics.
- Qualifications: 4-8 years of data engineering experience, especially in marketing analytics.
The predicted salary is between 50000 - 60000 £ per year.
A client in the luxury lifestyle and retail industry is seeking a Data Engineer to join the team for a 12 month fixed term contract. You will play a key role in establishing robust data foundations to support scalable, insight led marketing analytics across international markets. Reporting into a marketing analytics lead and working closely with data scientists, the objective of the project is to enable effective Marketing Mix Modelling and attribution through well governed, high quality and accessible data.
Responsibilities
- Design, build and maintain databases in Snowflake to support marketing analytics use cases
- Develop and manage scalable data pipelines connecting media, marketing, competitor and agency data sources
- Implement data governance standards, best practices and clear technical documentation
- Support Marketing Mix Modelling and Multi Touch Attribution initiatives across multiple countries
- Monitor, test and validate data to ensure accuracy, consistency and reliability
- Partner closely with data scientists to enable efficient model development and deployment
- Translate technical concepts into clear, business relevant outcomes for non technical stakeholders
- Support the adoption and effective use of Dataiku within the analytics workflow
Requirements
- 4–8 years’ experience in data engineering, ideally within marketing or media analytics
- Strong hands on experience with Snowflake (essential)
- Experience working with Dataiku (highly desirable)
- Solid understanding of marketing and media data and related analytics use cases
- Proven experience designing databases and building scalable, production ready data pipelines
- Strong knowledge of data governance, data quality monitoring and best practices
- Confident communicator, comfortable working in non technical and stakeholder facing environments
- Ability to translate business requirements into practical and effective data solutions
Details
- Duration: 12 months
- Day rate: Competitive, DOE
- Location: Hybrid, London (2 days per week in the office)
Data Engineer - Retail employer: Freshminds
Contact Detail:
Freshminds Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Retail
✨Tip Number 1
Network like a pro! Reach out to your connections in the luxury lifestyle and retail industry. Attend events, join relevant online groups, and don’t be shy about asking for introductions. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects, especially those involving Snowflake and Dataiku. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've implemented data governance and built scalable data pipelines. Practice translating complex concepts into simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly shows your enthusiasm and commitment to joining our team. Let’s get you that dream job!
We think you need these skills to ace Data Engineer - Retail
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Engineer in retail. Highlight your experience with Snowflake and any relevant projects that showcase your skills in marketing analytics. We want to see how you can bring value 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 engineering and how your background aligns with our needs. Don’t forget to mention your experience with Dataiku if you have it, as it’s highly desirable for us.
Showcase Your Technical Skills: When detailing your experience, be specific about the databases you've designed and the data pipelines you've built. We love seeing concrete examples of your work, especially those that relate to marketing mix modelling and data governance.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Freshminds
✨Know Your Data Tools
Make sure you brush up on your Snowflake and Dataiku skills before the interview. Be ready to discuss how you've used these tools in past projects, especially in relation to marketing analytics. This will show that you're not just familiar with the tech, but that you can apply it effectively.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data challenges in previous roles. Think about specific instances where you designed databases or built data pipelines. Being able to articulate your thought process will impress the interviewers and demonstrate your hands-on experience.
✨Communicate Clearly
Since you'll be working with non-technical stakeholders, practice explaining complex data concepts in simple terms. Use relatable examples to illustrate your points. This will highlight your ability to bridge the gap between technical and business needs, which is crucial for this role.
✨Understand the Business Context
Research the luxury lifestyle and retail industry, focusing on how data impacts marketing strategies. Be prepared to discuss how effective data governance and quality monitoring can drive better marketing outcomes. Showing that you understand the bigger picture will set you apart from other candidates.