At a Glance
- Tasks: Design and maintain scalable data pipelines for a global lifestyle brand.
- Company: Join a leading global lifestyle brand with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make an impact in the retail and luxury sectors while working with cutting-edge technology.
- Qualifications: Experience in retail or marketing, proficiency in Python and SQL, cloud knowledge required.
- Other info: Work 2-3 days a week in Central London with excellent career advancement potential.
The predicted salary is between 60000 - 75000 Β£ per year.
A global lifestyle brand is seeking a skilled Data Engineer to design and maintain scalable data pipelines, ensuring data quality and collaboration across teams.
The ideal candidate will have experience in retail or marketing, proficiency in Python and SQL, and cloud knowledge with AWS or GCP.
This hybrid role requires 2-3 days a week in the Central London office, offering a competitive salary of Β£60-75k per year.
Data Engineer: Marketing Data Pipelines (Retail/Luxury, Hybrid) employer: FRESHMINDS
Contact Detail:
FRESHMINDS Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Data Engineer: Marketing Data Pipelines (Retail/Luxury, Hybrid)
β¨Tip Number 1
Network like a pro! Reach out to folks in the retail and marketing sectors on LinkedIn. A friendly chat can open doors and give you insights into the company culture.
β¨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your data pipelines and projects. This is your chance to demonstrate your Python and SQL prowess.
β¨Tip Number 3
Practice makes perfect! Get ready for those technical interviews by brushing up on your cloud knowledge, especially AWS or GCP. We recommend mock interviews to boost your confidence.
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Engineer: Marketing Data Pipelines (Retail/Luxury, Hybrid)
Some tips for your application π«‘
Tailor Your CV: Make sure your CV highlights your experience in retail or marketing, especially any relevant projects involving data pipelines. We want to see how your skills in Python and SQL shine through!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for this role. Share specific examples of your work with data quality and collaboration across teams to grab our attention.
Show Off Your Cloud Knowledge: Since this role involves cloud technologies like AWS or GCP, donβt forget to mention any relevant experience you have. We love seeing candidates who are well-versed in these platforms!
Apply Through Our Website: We encourage you to apply directly through our website. Itβs the best way for us to receive your application and ensures youβre considered for this exciting opportunity!
How to prepare for a job interview at FRESHMINDS
β¨Know Your Data Pipelines
Make sure you can discuss your experience with designing and maintaining data pipelines. Be ready to share specific examples of how you've ensured data quality and collaborated with teams in previous roles, especially in retail or marketing.
β¨Brush Up on Python and SQL
Since proficiency in Python and SQL is key for this role, review your coding skills before the interview. Prepare to solve a few coding challenges or answer technical questions that demonstrate your expertise in these languages.
β¨Familiarise Yourself with Cloud Platforms
Whether it's AWS or GCP, make sure you understand the cloud services relevant to data engineering. Be prepared to discuss how you've used these platforms in past projects and how they can enhance data pipeline efficiency.
β¨Show Your Team Spirit
This role requires collaboration across teams, so be ready to talk about your teamwork experiences. Share examples of how you've worked with others to achieve common goals, particularly in a hybrid work environment.