At a Glance
- Tasks: Lead the design and build of scalable data systems for an AI-driven platform.
- Company: High-growth AI software company in London with a focus on innovation.
- Benefits: Competitive salary, career growth, and the chance to work with cutting-edge technology.
- Other info: Join a collaborative team and influence the technical direction as we scale.
- Why this job: Make a real impact by shaping the future of data engineering in a dynamic environment.
- Qualifications: Experience in data or backend engineering with strong Python and database skills.
The predicted salary is between 80000 - 100000 £ per year.
A high-growth AI software company is looking for a Lead Data Engineer to own and scale the data foundations behind an AI-driven operations platform used by property teams. This is a hands-on, high-ownership role where you'll define the data architecture, set engineering standards and build systems that power product analytics and modern AI capabilities.
What you'll do:
- Architect and build scalable data pipelines and distributed data systems
- Design ingestion, transformation and storage patterns for operational and AI workloads
- Deliver batch and real-time/streaming pipelines
- Build and optimise vector search and retrieval pipelines that support AI features
- Implement monitoring, observability and data quality frameworks
- Drive security, reliability and governance across the data layer
- Partner closely with backend and AI engineers to support training, inference and product delivery
- Influence technical direction and help shape the future data team as the company scales
What we're looking for:
- Demonstrable experience in data engineering or backend engineering with proven architecture ownership
- Good level of Python engineering skills
- Strong relational database experience (PostgreSQL preferred) including performance and query optimisation
- Exposure to NoSQL systems
Lead Data Engineer employer: FBI &TMT
FBI & TMT is an exceptional employer that fosters a dynamic and innovative work culture, perfect for professionals seeking to make a significant impact in the tech industry. With opportunities for growth and collaboration on cutting-edge projects, employees benefit from a flexible remote working environment complemented by occasional engagement at our London office. We prioritise employee development and offer competitive compensation, making this role not just a job, but a meaningful career path.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨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 FBI &TMT!
✨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 Lead Data Engineer at FBI &TMT.
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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 FBI &TMT.
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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 FBI &TMT, 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 FBI &TMT. 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 FBI &TMT
✨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 FBI &TMT!
✨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.
