At a Glance
- Tasks: Design and deliver data pipelines and AI applications that drive client decision-making.
- Company: Join fifty-five, a fast-growing data company part of The Brandtech Group.
- Benefits: Enjoy remote work flexibility, private medical coverage, and 25 days holiday.
- Other info: Be part of a multicultural team with excellent career growth opportunities.
- Why this job: Take ownership of projects and make a real impact with cutting-edge technology.
- Qualifications: Strong SQL and Python skills, experience with data pipelines and cloud platforms.
The predicted salary is between 72000 - 88000 £ per year.
Description
About the role
You'll design and deliver the data pipelines, platforms and AI applications that drive our clients' decision-making, working directly with them to turn business questions into production-ready systems on Google Cloud.
Our clients span different industries and sizes, from some of the world's biggest brands to fast-growing smaller businesses.
We give engineers real technical ownership.
You'll be the technical lead on your own projects and client accounts, trusted to make the calls and own the outcome.
You'll also be part of an engineering team that reviews each other's work and pitches in across projects.
On your accounts, you'll work day to day with fifty-five's consultants and data scientists.
You'll combine strong SQL, Python and cloud engineering with sound technical judgement, using AI tools to build faster and to a higher standard while keeping full ownership of what you deliver.
You'll also build AI applications for clients and for fifty-five's own teams, and help shape what we offer in data and AI.
What you'll do
- Design, build and operate scalable data pipelines, data models and end-to-end solution architectures on GCP (Big Query, Python, dbt, Airflow, Dataform), balancing reliability, maintainability, performance and cost.
- Own technical delivery on your projects and accounts, from scoping to production: making the design decisions, managing risks and dependencies, and communicating trade-offs clearly.
- Own the quality of what we deliver, with rigorous validation, automated testing, observability and data-quality controls built into production pipelines, and lead the diagnosis and fix when production issues come up.
- Design and build AI applications for clients and for fifty-five, such as LLM agents on Google Cloud with Gemini and Google's ADK.
Take them from prototype to production, with evaluation, cost control and secure handling of client data.
- Use agentic coding tools such as Claude Code or Codex to build faster and improve testing, checking their output critically and staying accountable for the result.
Share what works with the team as demos, docs and reusable patterns.
- Work with clients, consulting and data science teams to clarify requirements, challenge assumptions and turn business needs into pragmatic designs, and explain your reasoning to technical and non-technical people.
- Raise the team's engineering standards through design and code reviews, strong testing practices and clear documentation.
- What you'll bring
- Excellent SQL and strong Python skills.
- Proven experience designing, building and operating reliable data pipelines, data models and cloud platforms (GCP preferred, AWS or Azure also welcome), with transformation and orchestration tooling such as dbt, Airflow or Dataform.
- Strong software engineering practices: Git-based workflows, code review, automated testing and CI/CD.
- Hands-on experience building with LLMs (Gemini or similar), such as agents, connecting models to data and APIs, and evaluating outputs.
The judgement to know when to rely on AI-assisted engineering tools and when to verify.
- The ability to break down ambiguous problems, see the business challenge behind a task, make well-reasoned decisions, and prototype and pitch ideas for what we could build for clients.
- Excellent client-facing communication and confidence leading delivery independently: running several client projects at once and re-prioritising as client needs change, solo or within a larger project team.
Desirable experience
- Infrastructure as code (Terraform), cloud IAM, and secure handling of client data.
- Taking LLM agents to production: evaluation and guardrails, cost control, or making them available in Slack, Teams or similar tools.
- Applied data science (exploratory or statistical analysis), and dashboarding tools such as Looker or Power BI.
- Marketing platforms and an understanding of marketing data.
About the company
Part of The Brandtech Group, fifty-five is a data company helping brands collect, analyse and activate their data across paid, earned and owned channels to increase their marketing ROI and improve customer acquisition and retention.
Headquartered in Paris with offices in London, Hong Kong, New York and Shanghai, fifty-five is a certified Google Partner company and was named by Deloitte as one of the fastest-growing tech firms in Europe, thanks to its unique technology approach combining talent with software and service expertise.
If this sounds like you, please get in touch! We look forward to meeting you.
In return, we are pleased to offer you the following benefits
- Being part of a multicultural, dynamic and fast-growing team
- Continuous (and certified) training on the digital ecosystem and technologies (initial training for all new employees, followed by recurring training sessions)
- Private medical coverage through AXA
- Transport for London monthly travel card allowance
- The flexibility to work remotely for part of the week
- 25 days holiday per year, in addition to UK bank and public holidays
- Company pension plan
- Company-sponsored sporting and social activities
- Monthly Codecademy subscription - reimbursable upon completion of chosen training path fifty-five encourages diversity and is committed to guaranteeing equal treatment of all applications, regardless of gender, age, origin, sexual orientation, state of health or political or religious opinion.
Data Engineer (Data and AI) in London employer: Fifty-Five
fifty-five is an exceptional employer that fosters a dynamic and inclusive work culture, empowering its employees to drive innovation in the data and AI consultancy space. Located in London, the company offers unparalleled growth opportunities, allowing you to lead a talented team while collaborating with industry leaders and strategic partners. With a commitment to diversity and professional development, fifty-five provides a platform for meaningful contributions that shape the future of marketing technology.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Data and AI) in London
✨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 Fifty-Five!
✨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 Data Engineer (Data and AI) at Fifty-Five.
✨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 Fifty-Five.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer (Data and AI) at Fifty-Five, 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 Data Engineer (Data and AI) in London
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 Fifty-Five, 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 Fifty-Five. 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 Fifty-Five
✨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 Fifty-Five!
✨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.