At a Glance
- Tasks: Build and maintain data pipelines for AI systems, ensuring data quality and reliability.
- Company: Conquer AI, a fast-scaling tech company serving top global clients.
- Benefits: Fully remote work, competitive salary, equity options, and real ownership of your projects.
- Other info: Join a dynamic team where your work is truly valued and recognised.
- Why this job: Make a significant impact on AI systems that power major companies worldwide.
- Qualifications: Strong SQL and Python skills, experience with cloud platforms and data pipelines.
The predicted salary is between 60000 - 80000 £ per year.
Conquer AI deploys production-ready AI systems for FTSE 100, FTSE 250 and Fortune 500 clients. We're scaling fast. Every model we ship is only as good as the data underneath it, and right now that's the part nobody owns.
The reality of this role: Nobody notices good data infrastructure. Everybody notices bad data infrastructure, usually when a model gives a client the wrong answer with total confidence. You'll build and maintain the pipelines that feed our AI systems, structured and unstructured, batch and real time. You'll keep feature stores and vector databases consistent with what's actually true, so the engineers building on top of you aren't debugging your problem three layers up.
What you'll own:
- Data pipelines supporting the full AI lifecycle, from ingestion to model training to serving
- Feature stores and vector database consistency for retrieval and agentic systems
- Data quality, reliability and lineage across every pipeline you build
- Cloud data infrastructure and cost management on the platforms we run on
- Documentation that makes the data trustworthy to everyone downstream, including governance
Who you are:
- Strong in SQL and Python, with real pipeline experience, not just querying
- Comfortable with Spark or PySpark, dbt and Airflow for orchestration
- Experience with at least one major cloud platform (AWS, GCP or Azure)
- You've worked with vector databases or feature stores, or you pick them up fast
- You treat data reliability as an engineering discipline, contracts, observability, lineage, not an afterthought
- Fluent English, comfortable working async across a globally distributed team
Where you're coming from:
- Data Engineer or Senior Data Engineer at a tech company, scale-up or AI-focused team. You've built pipelines other people relied on without ever saying thank you. Now you want to build them somewhere that notices.
What we're offering:
- Real ownership of the data layer underneath every AI system we ship
- Fully remote, work from anywhere, any time zone
- Direct exposure to the infrastructure behind FTSE 100, FTSE 250 and Fortune 500 deployments
- Competitive package to include equity
If you'd rather fix the data than keep hearing it's the model's fault, we should talk. Message me, Farah, directly or apply.
PLEASE NOTE I personally review every CV, message and email I receive regarding our vacancies. While I read each one carefully, I'm unable to reply to everyone individually due to the volume of applications. Thank you for taking the time to apply and for your interest in working with us. Your effort is genuinely appreciated.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, 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 Conquer AI!
✨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 Senior Engineer, Data Engineering at Conquer AI.
✨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 Conquer AI.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Engineer, Data Engineering at Conquer AI, 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 Senior Engineer, 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 Conquer AI, 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 Conquer AI. 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 Conquer AI
✨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 Conquer AI!
✨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.
