At a Glance
- Tasks: Transform and govern data for impactful analytics across a fast-growing luxury brand.
- Company: Exciting, female-founded luxury brand committed to sustainability and ethical craftsmanship.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on AI tools and innovative data solutions.
- Why this job: Join a purpose-driven team making a real impact in the world of retail analytics.
- Qualifications: Strong SQL skills, dbt experience, and familiarity with GCP and BigQuery.
The predicted salary is between 50000 - 65000 £ per year.
THE BRAND This is one of the most exciting and purpose-driven accessible luxury brands in the world — female-founded, sustainability-led and commercially on fire across physical retail, eCommerce and global partnerships. Recognised as Responsible Business of the Year and consistently celebrated for its commitment to ethical craftsmanship and positive impact, this is a brand that genuinely stands for something beyond the product. With a loyal and growing global community at its heart and serious momentum across all channels, this is a business where the data team sits right at the centre of commercial decision-making — not on the periphery. For the right person, this is a rare opportunity to do meaningful, high-impact work inside a brand that the whole world has heard of and that people are genuinely proud to be part of.
THE ROLE This is a broad, end-to-end Analytics Engineer position sitting at the heart of the data value chain — bridging the gap between infrastructure and analytics delivery for a fast-growing global business. You will own the transformation and governance layer that powers dashboards, reporting and advanced analytics across the organisation — building and maintaining dbt models, managing cloud infrastructure on GCP and BigQuery, setting up data ingestion pipelines and championing data quality best practices throughout. This is not a siloed technical role — you will work closely with senior stakeholders across the business, take full ownership of projects from requirements through to delivery and bring a genuine data product mindset to everything you build. The team actively embraces AI tools in their day-to-day workflow and expects you to share that curiosity — whether that is using Claude or GitHub Copilot to accelerate development, experimenting with conversational data interfaces or thinking about what AI means for the future of analytics. Small team, big ownership, real commercial impact.
THE PERSON You are a technically strong, commercially curious Retail Analytics/Data Engineer who thrives at the intersection of engineering rigour and analytical thinking — someone who builds clean, reliable data models but never loses sight of the business question behind the request. You have a strong command of SQL and hands-on dbt experience, practical knowledge of cloud data platforms — ideally GCP and BigQuery — and familiarity with data ingestion tools including Fivetran, Python and API integrations. You are equally comfortable working with senior stakeholders as you are in the codebase, you take ownership without being asked and you bring genuine curiosity about how AI is changing the way data teams work. A background in retail, DTC or eCommerce is strongly preferred — and above all you are the kind of person who collaborates openly, communicates with clarity and brings energy and humility to a high-performing team.
Analytics Engineer in Slough employer: WeComm
As a leading accessible luxury brand, we pride ourselves on being a purpose-driven employer that champions sustainability and ethical craftsmanship. Our dynamic work culture fosters collaboration and innovation, providing Analytics Engineers with the opportunity to make a significant impact on commercial decision-making while working closely with senior stakeholders. With a commitment to employee growth and a supportive environment that embraces cutting-edge AI tools, this is an exceptional place for those looking to thrive in a meaningful role within a globally recognised brand.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in Slough
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like WeComm!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytics Engineer at WeComm.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like WeComm.
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at WeComm, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Analytics Engineer in Slough
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at WeComm, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at WeComm. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at WeComm
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at WeComm!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
