At a Glance
- Tasks: Build scalable data pipelines and onboard datasets for analytics and operational workflows.
- Company: Join Rimes, a leader in enterprise data management solutions for the investment community.
- Benefits: Enjoy 28 days of leave, gym discounts, health plans, and flexible hybrid work.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make an impact by solving complex data problems with cutting-edge technology.
- Qualifications: 1-3 years in data engineering, proficiency in Python, PySpark, and SQL.
The predicted salary is between 50000 - 70000 £ per year.
About Rimes Rimes provides enterprise data management solutions to the global investment community. Driven by our passion for solving the most complex data problems, we provide our clients with investment intelligence that powers more than US$75 trillion in assets under management annually. The world’s leading institutional investors, asset managers and service providers rely on Rimes to help them make better investment decisions using accurate information and industry-leading technology.
The Opportunity: We’re looking for a Data Engineer to own data onboarding and build scalable, reliable data pipelines that power analytics, operational workflows, and data‑driven decisions across Rimes. You’ll work closely with data producers, analysts, and product teams to ingest, transform, and operationalize data, primarily within Palantir Foundry (our core data platform) and complementary cloud compute. Note: Experience with Palantir Foundry is a strong plus but not required. If you bring solid data engineering fundamentals in Python/PySpark, SQL, and modern ELT patterns, we’ll support a fast ramp‑up on Foundry.
Responsibilities:
- Ingest & onboard datasets from internal systems, APIs, databases, files, external providers, and real‑time feeds.
- Build and operate scalable ETL/ELT pipelines using Python, PySpark, SQL, and Foundry pipeline tooling; schedule and automate batch/stream refreshes.
- Model and operationalize data (e.g., defining entities/relationships) to support analytics and operational applications in collaboration with domain experts.
- Ensure trust in data through testing, data quality checks, observability/alerting, lineage, and compliant access controls.
- Collaborate with analysts and product teams to translate business requirements into robust data solutions and clear data contracts/SLOs.
What Success Looks Like (First 3–6 Months):
- You onboard and productionize new data sources with reliable refresh (scheduled or real‑time).
- You deliver trusted, well‑documented datasets consumed by analytics and operational teams.
- Key business entities are clearly modeled and discoverable.
- Pipelines have meaningful monitoring and alerting, with reduced failures/re‑runs.
- You contribute to standards/templates that speed up future onboarding.
Requirements:
- 1-3 years in data engineering or analytics engineering with end‑to‑end pipeline delivery in production.
- Proficiency in Python & PySpark for distributed data processing.
- Strong SQL for analytical and transformation logic.
- Data modeling skills for both analytics and operational use cases.
- Experience with data ingestion from APIs, databases, external feeds, and real-time sources.
- Solid grasp of data quality, testing, observability, lineage, and governance practices.
- Comfort working with large datasets and distributed compute using modern ELT patterns.
Nice To Have:
- Palantir Foundry: pipelines/transforms, Code Repos, Ontology, and operational applications.
- Spark execution concepts: partitions, shuffles, caching, and performance optimization.
- Exposure to Databricks or cloud‑native compute with compute pushdown.
- Experience with financial or enterprise operational data.
- Experience with AI‑assisted ETL/ELT or data quality tooling.
- Familiarity with streaming frameworks and/or orchestration tools.
What We Offer:
- 28 days of annual leave
- AXA Gym Membership Discount
- Healthshield Cashback plan
- Healthshield Perks platform (Breeze)
- MetLife Afterlife Support
- Metalife GP 24 hour virtual GP service
- Annual ‘purchase holiday’ scheme
- Chubbs Travel Insurance
Compensation: Competitive pay and bonus eligibility
Work Life Balance: Flexible hybrid work environment
Only selected candidates will be contacted for interviews. We appreciate your understanding. Thank you for considering a career with us. Rimes is committed to promote the values of diversity and inclusion throughout the business. Whether it’s through recruitment, retention, career progression or training and development, we are committed to improving opportunities for people regardless of their background or circumstances. Visit our Careers page to see our complete listings.
Data Engineer in London employer: Rimes Technologies
Rimes is an exceptional employer that fosters a collaborative and innovative work culture, where Data Engineers are empowered to shape the future of our data platform. Located in a vibrant tech hub, we offer competitive benefits, continuous learning opportunities, and a commitment to employee growth, ensuring that you can thrive both personally and professionally while contributing to cutting-edge AI-driven projects.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Rimes on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. Personal connections can give you an edge!
✨Tip Number 2
Prepare for technical interviews by brushing up on your Python, PySpark, and SQL skills. Practice coding challenges and data modelling scenarios that are relevant to the role. We want to see you shine with your data engineering fundamentals!
✨Tip Number 3
Showcase your projects! If you've built any data pipelines or worked on relevant projects, be ready to discuss them in detail. Highlight how you tackled challenges and what technologies you used. This is your chance to impress us!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Rimes. Let’s get you on board!
We think you need these skills to ace Data Engineer 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 Python, PySpark, and SQL, and don’t forget to mention any relevant projects or achievements that showcase your data engineering skills.
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 skills align with Rimes' mission. Be sure to mention any experience with data onboarding and pipeline building.
Showcase Your Problem-Solving Skills:Rimes loves problem solvers! In your application, share examples of how you've tackled complex data challenges in the past. This will demonstrate your ability to contribute to our mission of providing investment intelligence.
Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s super easy, and you’ll be able to see all the details about the role and our company culture!
How to prepare for a job interview at Rimes Technologies
✨Know Your Data Engineering Fundamentals
Brush up on your Python, PySpark, and SQL skills before the interview. Be ready to discuss how you've used these technologies in past projects, especially in building ETL/ELT pipelines. This will show that you have a solid foundation and can hit the ground running.
✨Familiarise Yourself with Rimes' Data Solutions
Take some time to understand Rimes' enterprise data management solutions and how they serve the investment community. Knowing their products and how they leverage data will help you align your answers with their business goals during the interview.
✨Prepare for Technical Questions
Expect technical questions related to data ingestion, transformation, and operationalisation. Prepare to explain your approach to ensuring data quality and governance. Practising common data engineering scenarios can help you articulate your thought process clearly.
✨Show Your Collaborative Spirit
Rimes values collaboration with analysts and product teams. Be ready to share examples of how you've worked with others to translate business requirements into data solutions. Highlighting your teamwork skills will demonstrate that you're a good fit for their culture.
