At a Glance
- Tasks: Build scalable data solutions and maintain data pipelines for analytics and AI applications.
- Company: Prolific, a leader in human data infrastructure for AI development.
- Benefits: Competitive salary, remote work, and a mission-driven culture.
- Other info: Collaborative environment with opportunities for groundbreaking research.
- Why this job: Join us at the forefront of AI innovation and make a real impact.
- Qualifications: 3+ years in data engineering, strong SQL and Python skills, and cloud-native experience.
The predicted salary is between 63000 - 77000 £ per year.
- Data Engineer
- Prolific
Prolific is not just another player in the AI space—we are the architects of the human data infrastructure that's reshaping the landscape of AI development.
In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models.
The role
We're looking for a Data Engineer to help build scalable data solutions that serve teams across the business—from data scientists and analysts to AI engineers and product teams.
You'll contribute to both the underlying platform and the way data is used in our products, working in a modern, cloud-native environment where privacy, security, and good data practices are part of how we build.
- What you’ll bring to the role
- Technical
Expertise: 3+ years building and shipping production-grade data systems, with strong SQL skills and proficiency in Python or another object-oriented language (Java, Scala etc.)
- Familiarity with cloud-native infrastructure—ideally some exposure to Terraform, Kubernetes, or similar Ia C and container orchestration tools.
We don't expect deep expertise in all of these, but comfort working in this kind of environment matters.
- Experience designing data APIs or services that expose data to applications, or a strong interest in working across the analytical/operational boundary.
- A thoughtful approach to data quality, privacy, and security—you understand that how data is used is as important as how it's moved.
- Strong collaboration skills and comfort working across teams with different priorities—engineers, data scientists, AI engineers, and product.
- A pragmatic, curious mindset—you enjoy keeping up with the field and know when to reach for a new tool versus when to stick with what works.
- Pipeline Management: Hands-on experience with data pipeline tools (Airflow, dbt) and strong ability to optimize for performance and reliability.
- Quality Focus: Commitment to continuously improving product quality, security, and performance through rigorous testing and code reviews.
- Documentation: Meticulous approach to creating and maintaining architecture and systems documentation.
- Problem-Solving: Exceptional analytical skills to troubleshoot complex data issues and implement effective solutions.
- Independence: Capability to ship medium features independently while contributing to the team's overall objectives.
- What you’ll be doing in the role
- Build and maintain data pipelines that power analytics, ML workloads, and product-facing applications—from internal databases, Saa S sources, and streaming systems through to the teams and services that consume them.
- Evolve our data platform alongside cloud platform engineers, using infrastructure-as-code (Terraform) and Kubernetes-based deployments (Argo) to keep the platform scalable, reliable, and self-serve.
- System Architecture: Design and implement scalable data infrastructure that accommodates our growing data volume and complexity.
- Develop data services and APIs that expose trusted data to product applications, bridging analytical and operational systems.
- Own data quality and observability, putting monitoring, testing, and alerting in place so issues are caught early and trust in the data stays high.
- Partner with AI engineers, data scientists, analysts, and product teams to understand their data needs and design the right solutions—not just the quickest ones.
- Uphold strong data privacy, security, and compliance practices in everything you build, particularly where data flows into product-facing contexts.
- Technical Documentation: Create and maintain comprehensive documentation of data flows, models, and systems for knowledge sharing.
- Security and Compliance: Ensure all data systems adhere to security best practices and compliance requirements.
- Why Prolific is a great place to work
We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioral data and feedback.
This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
We believe that the next leap in AI capabilities won't come solely from scaling existing models but from integrating diverse human perspectives and behaviors into AI development.
By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation—one that reflects the breath and the best of humanity.
Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research.
Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.
Links to more information on Prolific
Benefits
- External Handbook
- Website
- You Tube
- Privacy Statement
By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organization planning. Prolific's
Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
Data Engineer employer: Prolific
Prolific is an exceptional employer that places you at the cutting edge of AI innovation, offering a unique opportunity to work on multimodal data collection that shapes the future of technology. With a mission-driven culture, competitive salary packages, and a commitment to employee growth, Prolific fosters an inclusive environment where your contributions directly impact groundbreaking research. Enjoy the flexibility of remote working while being part of a team dedicated to ethical data practices and diverse human perspectives.
StudySmarter Expert Advice🤫
We think this is how you could land 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 Prolific!
✨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 at Prolific.
✨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 Prolific.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Prolific, 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
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 Prolific, 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 Prolific. 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 Prolific
✨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 Prolific!
✨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.
