Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Support and optimise data pipelines and AI workflows on Palantir Foundry.
- Company: Join a leading analytics firm in the heart of London.
- Benefits: Enjoy a competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Be at the forefront of data engineering and make a real impact in production environments.
- Qualifications: 5+ years in Data Engineering with strong Palantir Foundry experience.
- Other info: Collaborative team environment with a focus on innovation and stability.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for an experienced Palantir Data Engineer to provide production support for data pipelines, AI‑enabled workflows, and applications built on Palantir Foundry. This role is focused on ensuring the stability, availability, and performance of production data systems by proactively monitoring workflows, resolving incidents, and supporting operational excellence across the Foundry platform.
You will work closely with data engineers, platform teams, and business stakeholders to troubleshoot issues, debug AI model outputs, and continuously improve system reliability in a live production environment.
Key Responsibilities- Provide production support for Palantir Foundry components including pipelines, Ontology, AIP Logics, API integrations, and applications.
- Monitor end‑to‑end workflows, identify failures, and resolve issues within agreed service levels.
- Troubleshoot data ingestion, extraction, transformation, and orchestration issues across complex pipelines.
- Collaborate with cross‑functional teams to resolve production incidents and improve overall system stability.
- Perform root cause analysis (RCA) and implement preventative and corrective measures.
- Manage and maintain data quality checks to ensure data integrity across production systems.
- Support deployments, release management, and ongoing environment maintenance.
- Develop and maintain clear documentation for support processes, operational procedures, and known issues.
- Strong hands‑on experience with Palantir Foundry, including Code Repositories, Workshop, AIP Logic, and Automate.
- Proficiency in Python and PySpark or TypeScript.
- Experience working with AWS services such as S3, Lambda, Glue, and related data services.
- Solid understanding of data pipeline architectures, ETL processes, and production data workflows.
- Proven experience working in production support or operational data engineering environments.
- Familiarity with Generative AI–enabled workflows, API integrations, and orchestration patterns.
- Strong problem‑solving skills with the ability to communicate clearly with both technical and non‑technical stakeholders.
- Additional experience with Foundry, AIP, and PySpark.
- Knowledge of monitoring, alerting, and logging tools and frameworks.
- Exposure to TypeScript/React for Workshop applications and workflow orchestration.
- Experience working within the insurance domain.
- 5+ years of experience in Data Engineering, with demonstrable experience in production support roles.
- 2+ years of hands‑on experience delivering and supporting solutions on Palantir Foundry.
Data Engineer (Palantir) in London employer: Experis
Contact Detail:
Experis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Palantir) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who have experience with Palantir. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Get your hands dirty with practical projects. Showcase your skills in Python, PySpark, and AWS by working on personal or open-source projects. This not only boosts your portfolio but also gives you real-world examples to discuss in interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice common data engineering scenarios and be ready to demonstrate your troubleshooting abilities, especially around production support and data pipelines.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Engineer (Palantir) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Palantir Foundry, Python, and AWS services. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background makes you a perfect fit for our team at StudySmarter. Keep it engaging and relevant!
Showcase Your Problem-Solving Skills: In your application, don’t forget to mention specific examples of how you've tackled challenges in production support or data workflows. We love seeing how you approach problem-solving and improve system reliability.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Experis
✨Know Your Palantir Inside Out
Make sure you brush up on your knowledge of Palantir Foundry, especially the components like Code Repositories and AIP Logic. Be ready to discuss your hands-on experience and how you've used these tools in past roles.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled production support issues. Think about times when you performed root cause analysis or improved system stability, and be ready to explain your thought process.
✨Familiarise Yourself with AWS Services
Since this role involves working with AWS services like S3 and Lambda, make sure you can talk about your experience with these tools. Highlight any projects where you've integrated AWS into your data pipelines.
✨Communicate Clearly with All Stakeholders
Practice explaining complex technical concepts in simple terms. You'll need to collaborate with both technical and non-technical teams, so being able to communicate effectively is key to success in this role.