Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to enhance data infrastructure and support analytics.
- Company: Be part of a high-growth beauty brand disrupting the industry.
- Benefits: Enjoy a competitive salary and work in a vibrant London office four days a week.
- Why this job: Contribute to impactful data-driven decisions in a fast-paced, innovative environment.
- Qualifications: Experience with SQL, Python, GCP, and dbt is essential.
- Other info: This role offers a chance to grow your skills in a supportive team.
The predicted salary is between 48000 - 52000 £ per year.
We are working with a high-growth company looking for a Junior/Mid Data Engineer to join their dynamic team. This is a great opportunity to work with an established data warehouse and help advance their data infrastructure to support analytics and reporting at scale. This is a disruptive challenger in the beauty brand industry that is in a phase of huge growth.
Key Responsibilities:
- Enhancing and optimising the data warehouse and pipeline architecture.
- Developing scalable and efficient data models and integrations.
- Improving ETL/ELT processes, focusing on automation and reliability.
- Driving data governance, data quality, and best practices across the organisation.
- Collaborating with cross-functional teams to ensure impactful data-driven decision-making.
Tech Stack: SQL, Python, GCP, dbt
Location: London Office - 4 Days a week in the office
Salary: 60k - 65k
Data Analytics Engineer employer: Guillaume Masson
Contact Detail:
Guillaume Masson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics Engineer
✨Tip Number 1
Familiarise yourself with the specific tech stack mentioned in the job description, especially SQL and Python. Consider working on personal projects or contributing to open-source projects that utilise these technologies to showcase your skills.
✨Tip Number 2
Network with professionals in the data analytics field, particularly those who work in the beauty industry. Attend relevant meetups or webinars to gain insights and potentially get referrals that could help you land the job.
✨Tip Number 3
Prepare to discuss your experience with data governance and quality assurance during interviews. Be ready to share examples of how you've implemented best practices in previous roles or projects.
✨Tip Number 4
Research the company’s current data infrastructure and any recent developments in their analytics capabilities. This will allow you to ask informed questions during the interview and demonstrate your genuine interest in their growth.
We think you need these skills to ace Data Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with SQL, Python, and GCP. Showcase any projects or roles where you've enhanced data warehouses or optimised ETL processes.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for data analytics and the beauty industry. Mention specific examples of how you've contributed to data governance and quality in previous roles.
Highlight Technical Skills: Clearly list your technical skills related to the job description, such as your proficiency in SQL, Python, and dbt. If you have experience with GCP, make sure to emphasise that as well.
Showcase Collaboration Experience: Since the role involves working with cross-functional teams, include examples of past collaborations. Describe how your contributions led to impactful data-driven decisions in those scenarios.
How to prepare for a job interview at Guillaume Masson
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL, Python, and GCP during the interview. Be prepared to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Understand Data Warehousing Concepts
Familiarise yourself with data warehousing principles and best practices. Be ready to explain how you would enhance and optimise a data warehouse, and discuss your approach to developing scalable data models.
✨Emphasise Collaboration
Since the role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated with others in previous roles. Highlight your communication skills and ability to drive data-driven decision-making.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially related to ETL/ELT processes. Think of scenarios where you improved automation and reliability, and be ready to discuss your thought process and the outcomes.
