At a Glance
- Tasks: Lead WGSN's data platform, shaping architecture and integrating diverse data sources.
- Company: Join a forward-thinking company at the forefront of data innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting challenges and career advancement opportunities.
- Why this job: Make a significant impact by leading AI-driven data initiatives and innovative projects.
- Qualifications: 10+ years in data engineering with leadership experience and strong technical skills.
The predicted salary is between 90000 - 110000 £ per year.
We're hiring a Director of Data Engineering to own WGSN's data platform: its architecture, its data models and how it runs day to day. You'll report to our Group Chief Data Officer, lead a team of five data engineers, and work closely with our Group Technology, Data Science and programme teams. At the heart of the role is the trend spine, the connected backbone that links trend signals, taxonomies, forecasts and content. Next year we launch an expanded social data product across TikTok, Reddit and Instagram, and after that we plan to rebuild the platform. You'll lead both, and lay the data foundations for the AI products that will sit on top.
What You’ll Do
- Own data architecture and modelling across the WGSN platform
- Design and build the trend spine
- Integrate structured, semi-structured and unstructured data, from social and search signals to runway imagery and proprietary research
- Lead, develop and set standards for a team of five engineers, plus agency and contractor partners
- Lead architecture discussions with our Group Technology team
- Shape the planned platform rebuild, including stack, cost and vendor decisions
- Introduce AI-assisted and agentic engineering practices and build AI-ready data foundations
- Make sure the platform is reliable, well governed, GDPR compliant and cost effective
What We're Looking For
- Experience designing or substantially reshaping a data platform, with clear ownership of architecture and modelling decisions
- The technical depth and confidence to lead engineering and architecture conversations with senior technologists
- Data engineering leadership at a small to mid-size business, or at manager level in a larger organisation with real design ownership
- Hands-on experience with semi-structured and unstructured data alongside structured data
- A practical track record of using AI to change how your team builds
Nice to Have
- Snowflake, Databricks and AWS
- Embeddings, vector search, feature stores or knowledge graphs
- Taxonomy or ontology design
- Social, web-scale or licensed third-party data
- A background in media, information services, SaaS or e-commerce
Experience
- Around 10 or more years in data engineering, with at least four years leading engineers.
Director of Data Engineering employer: Academic Key
Deliveroo is an exceptional employer that prioritises the well-being of its employees while fostering a culture of innovation and collaboration. With a commitment to diversity and inclusion, we offer competitive benefits tailored to each country, including generous leave allowances and support for charitable causes. As part of a rapidly growing global team, you'll have the opportunity to work on impactful projects that shape the future of customer support, all while enjoying a dynamic and supportive work environment.
StudySmarter Expert Advice🤫
We think this is how you could land Director of Data Engineering
✨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 Academic Key!
✨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 Director of Data Engineering at Academic Key.
✨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 Academic Key.
✨Apply Directly through Our Website
When you find a suitable opening like Director of Data Engineering at Academic Key, 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 Director of Data Engineering
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 Academic Key, 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 Academic Key. 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 Academic Key
✨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 Academic Key!
✨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.
