At a Glance
- Tasks: Architect and build scalable data infrastructure for impactful insights and models.
- Company: Join Code and Theory, a leading digital-first creative agency.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a mix of tech and creative talent.
- Why this job: Shape data strategy and culture while working with top-tier clients and innovative projects.
- Qualifications: 5+ years in data engineering, strong Python and SQL skills, and mentoring experience.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking an experienced Lead Data Engineer to architect and build scalable data infrastructure that powers data-driven insights and predictive and generative models. The ideal candidate will be a product-minded technologist, practiced in translating business needs into elegant technical solutions. They will have broad purview to establish best practices, and lay the foundation for a world-class data organization. As a lead engineer, they will get to work cross-functionally with stakeholders across the agency, have significant autonomy in technical decision-making, and play a pivotal role in shaping our data strategy and data engineering team culture.
WHAT YOU'LL NEED
- 5+ years experience in data engineering, with demonstrated experience designing, building, and scaling data pipelines and infrastructure from the ground up
- Strong product orientation, with proven ability to identify opportunities, prioritize initiatives, and deliver data solutions that drive measurable business value
- Deep expertise in cloud data platforms
- Proficiency in Python and SQL both for data processing and ETL, as well as for closely collaborating with the Machine Learning Engineering team
- Track record of mentoring engineers and establishing engineering standards, documentation, and best practices
- Familiarity with marketing data ecosystems (GA4, advertising platforms, CRMs, CDPs)
- Great communication, and an ability to communicate with the spectrum of technical levels present at an organization like Code and Theory, which is 50/50 Tech/Creative
NICE TO HAVE
- Experience with data governance, privacy compliance, and security best practices
- Experience integrating AI/ML capabilities into data pipelines; exposure to GenAI applications
ABOUT US
Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic. Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok. The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.
Lead Data Engineer (London) (Hiring Immediately) employer: Code and Theory
At Code and Theory, we foster a dynamic work culture that thrives on creativity and collaboration, making it an exceptional place for a Lead Data Engineer to grow. With significant autonomy in technical decision-making and the opportunity to mentor fellow engineers, you will play a crucial role in shaping our data strategy while working alongside a diverse team of talented professionals. Located in London, we offer a vibrant environment that encourages innovation and provides access to a global network of industry leaders, ensuring meaningful and rewarding career development.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer (London) (Hiring Immediately)
✨Get Involved in Data Challenges
Participate in data challenges like Kaggle competitions or DrivenData to showcase your skills and network with other data enthusiasts. Not only will you build your portfolio, but you can also catch the eye of potential employers like Code and Theory.
✨Connect with Local Data Communities
Join local data science meetups or online communities like Data Science Society to engage with professionals in the field. These platforms are great for networking, discovering job opportunities, and keeping your fingers on the pulse of industry trends.
✨Leverage Your University’s Resources
If you're still in university, make full use of your career services. They might have part-time roles tailored for students like you, and often have direct connections with companies looking to hire talented interns in data science roles.
✨Apply Directly Through Our Website
Don’t forget to check out our jobs at Code and Theory and apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate individuals like us who are eager to make an impact in the data science world.
We think you need these skills to ace Lead Data Engineer (London) (Hiring Immediately)
Some tips for your application 🫡
Show Your Data Skills:In your CV, make sure to highlight your proficiency with key data analysis tools and programming languages like Python, R, or SQL. We want to see that you've got hands-on experience with data manipulation and visualisation, so if you've worked on any relevant projects or coursework, include those details to really showcase your skills!
Tailor Your Projects Towards Data Science:When it comes to your portfolio, focus on showcasing projects that highlight your data-science abilities. Include analyses, dashboards, or any predictive models you've built. If you've contributed to Kaggle competitions or have a GitHub repository with data projects, make sure to link those—these demonstrate your practical experience and problem-solving abilities.
Express Your Motivation in the Cover Letter:Since this is a part-time role, we want to know why you're particularly interested in juggling this with your other commitments. Use your cover letter to express your passion for data science and how this role at Code and Theory aligns with your career aspirations. Show us you're excited about learning and growing with us!
Keep It Concise Yet Informative:Part-time positions often receive many applications, so keep your documents clear and to the point! Aim for a concise CV detailing your relevant experiences without unnecessary fluff. Be sure to include your availability in your cover letter as well—that helps us in the decision-making process!
How to prepare for a job interview at Code and Theory
✨Brush Up on Your Stats!
Given you're eyeing a part-time role in data science, make sure you’re on top of your statistical methods and data analysis techniques. Expect questions around regression, hypothesis testing, and maybe even some statistical programming languages like R or Python during the interview with Code and Theory.
✨Show Off Your Projects!
It's crucial to have a portfolio that showcases your data science projects. Highlight your part-time work with specific data sets, models you've built, or analyses you've conducted. Having tangible examples will demonstrate your hands-on experience and problem-solving skills to Code and Theory.
✨Familiarise Yourself with Tools of the Trade
Make sure you’re well-versed in data science tools like Jupyter Notebook, Tableau, or SQL. You might get technical questions or even a practical test at Code and Theory, so having a comfort level with these tools will definitely be an advantage.
✨Be Ready to Discuss Real-World Applications
Since this is a part-time role, employers at Code and Theory will likely appreciate your understanding of how data science can address actual business problems. Be prepared to discuss any relevant case studies or how you would approach specific challenges in real scenarios.
