At a Glance
- Tasks: Lead the data team in building and optimising scalable data pipelines and AI solutions.
- Company: Join a forward-thinking company at the forefront of AI and data engineering.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Thriving culture that values innovation, collaboration, and personal development.
- Why this job: Make a real impact by shaping the future of data and AI in a dynamic environment.
- Qualifications: 5+ years in data engineering with expertise in AI/ML applications and cloud platforms.
The predicted salary is between 70000 - 90000 £ per year.
You will join our Data team as owner of our data infrastructure with an opportunity to architect and own the data pipelines, platforms and practices that will power our Data Platform. A key part of this role is improving and defining how stakeholders can use AI to self‑serve their own analysis. You’ll sit at the intersection of data engineering and applied AI, working closely with analytics engineers and analysts. You will define the standards and systems that allow the data team and stakeholders to self‑serve analysis using AI as a base— ensuring the data foundation is reliable, scalable and ready to fuel our AI and LLM capabilities.
What you’ll do:
- Build and maintain scalable data pipelines to ingest, transform and integrate data from multiple sources, defining best practice along the way.
- Implement robust monitoring for data ingestion jobs and take swift corrective action when issues arise.
- Work with business stakeholders to translate requirements into efficient pipeline architectures, database structures and optimised data models.
- Partner with analytics engineers to ensure clean, accessible data is available to analysts across the organisation.
- Champion responsible AI principles in the design and deployment of data systems that underpin our LLM and RAG implementations.
- Lead on development standards, version control, quality control, deployment and change management processes.
- Monitor, measure and maintain high data quality standards across all data products and pipelines.
Who you are:
- AI & LLM expertise: Experience building and deploying AI/ML‑powered applications. A solid understanding of responsible AI principles and how they apply to data infrastructure and product development.
- Data engineering foundation: 5+ years of commercial experience as a data engineer across multiple data products and pipelines. Advanced knowledge of GCP as a data warehouse. Advanced SQL skills with the ability to design and optimise complex queries at scale. Deep familiarity with modern analytics and data architectures, including data warehousing best practices. Experience with scalable backend systems and cloud platforms, with comfort across the full data engineering lifecycle — ingestion, cleaning, transformation and integration. Experience with dbt, Fivetran and Snowflake. Python proficiency. Previous experience in health, wellness, pharmaceutical or digital/e‑commerce sectors.
How you work:
- Customer‑focused: you are genuinely excited about building products that drive positive change at scale.
- Self‑starter: you use your own initiative, anticipate problems before they arise and take full ownership from raw ingestion to final delivery.
- Pragmatic problem‑solver: you take genuine pleasure in finding the right solution and making sensible trade‑offs under real‑world constraints.
- Growth mindset: you thrive in fast‑paced scale‑up environments and are energised, not unsettled, by ambiguity and pace.
Lead Data Engineer London employer: Meeveem Limited
As a Lead Data Engineer in London, you will be part of a dynamic and innovative data team that champions a culture of collaboration and continuous improvement. Our commitment to employee growth is reflected in our supportive environment, where you will have the opportunity to architect cutting-edge data solutions while leveraging AI to empower stakeholders. With a focus on responsible AI principles and a fast-paced scale-up atmosphere, we offer a unique chance to make a meaningful impact in the health, wellness, and digital sectors.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer 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 Meeveem Limited!
✨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 London at Meeveem Limited.
✨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 Meeveem Limited.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer London at Meeveem Limited, 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 Lead Data Engineer 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 Meeveem Limited, 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 Meeveem Limited. 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 Meeveem Limited
✨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 Meeveem Limited!
✨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.
