At a Glance
- Tasks: Build data pipelines and automate workflows for cutting-edge materials science projects.
- Company: Join a pioneering tech company focused on AI and materials discovery.
- Benefits: Competitive salary, equity options, generous holiday, and parental leave.
- Other info: Collaborative environment with opportunities for professional growth and learning.
- Why this job: Make a real impact in sustainability and climate solutions through innovative technology.
- Qualifications: 3+ years in data engineering, strong Python skills, and experience with large datasets.
The predicted salary is between 60000 - 75000 € per year.
The Role
As we grow, we are seeking a Data Engineer to play a crucial part in driving our research and development efforts forward.
Your Impact
As a Data Engineer you will be part of the new team building the infrastructure that underpins and acts as the critical bridge between raw chemical data and our machine learning models.
What You Will Do
- Data Pipeline Development
- Design and build robust data pipelines for materials science datasets, experimental results, and computational chemistry outputs.
- Develop processes to integrate diverse data sources including materials databases, literature, patent filings, and laboratory instruments.
- Create automated workflows for processing crystallographic data, molecular structures, and materials properties (you don’t need to have direct domain experience - we can help bring you up to speed!).
- Build scalable systems to handle high-throughput computational chemistry calculations and experimental data.
- Data Quality & Standardisation
- Partner closely with the scientific and research teams to implement automated quality checks for crystal structure data, chemical compositions, and experimental measurements.
- Create standardisation protocols for materials nomenclature, units, and measurement conditions.
- Build monitoring systems to ensure data integrity across all pipelines.
- Collaboration & Integration
- You will also be working hand in hand with ML researchers to understand data requirements for model training and inference.
- Partner with materials scientists to ensure accurate representation of domain knowledge in data schemas.
- Integrate with laboratory automation systems and computational chemistry software.
- Support real-time data needs for AI-driven materials discovery experiments.
Must Have Skills and Qualifications
- You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that Cusp is building.
- You’re a builder of tools and infrastructure who enjoys making life as easy as possible for the teams, providing self‑serve, reliable and scalable ingestion pipelines.
- You have at least 3+ years experience in data engineering roles, preferably in scientific or research environments - you would be joining as a data engineering subject matter expert who can not only work autonomously but also provide guidance on best practice.
- High level of proficiency in Python and databases with experience in large‑scale data processing - as part of our engineering team you’ll be programming regularly, not just scripting.
- You’re an advanced user of workflow orchestration tools (e.g. Airflow, Prefect, Dagster, Flyte or similar).
- Solid experience with containerisation (Docker, Kubernetes) and CI/CD practices.
- You have direct experience handling large/complex datasets and are interested in working with scientific packages.
- You’re a fast learner when it comes to new tools/systems.
- You enjoy (and have experience in) designing systems that scale with growing data volumes and user demands.
- Understanding and appreciation of DevOps practices is also important.
Bonus Points (But Not Critical)
- You’ve worked with data from scientific computing (simulations or experiments).
- Knowledge of machine learning data requirements and MLOps practices, including pre-processing/processing as part of model training.
- An academic background in Materials Science, Chemistry, Chemical Engineering, or related field.
- Even more bonus points if you have an understanding of crystallography, materials properties, and computational chemistry concepts!
What we Offer
- Competitive salary: We value and reward impact and growth.
- Equity in CuspAI: You have a stake in the success of the company.
- Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays.
- ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together.
- Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth.
- Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate‑related problems through the creation and application of bleeding‑edge SOTA technology and revolutionary techniques.
- True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world‑class researchers and engineers who enjoy sharing knowledge and supporting each other.
CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
Data Engineer employer: CuspAI
CuspAI is an exceptional employer that fosters a collaborative and innovative work culture, where Data Engineers play a pivotal role in advancing materials science through cutting-edge technology. With a competitive salary, equity options, generous holiday allowances, and a strong commitment to professional development, employees are empowered to grow their skills while contributing to meaningful projects that address sustainability challenges. The inclusive environment encourages diverse perspectives, making it a rewarding place for those passionate about scientific discovery and technological advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipeline projects or any relevant work you've done. This gives you a chance to demonstrate your expertise and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s mission. Be ready to discuss how your experience aligns with their goals, especially in building scalable systems and ensuring data quality.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at CuspAI.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your data pipeline development experience and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to show us your passion for materials science and data engineering. Share why you're excited about this role and how your background aligns with our goals. Let your personality shine through!
Showcase Your Technical Skills:Be specific about your proficiency in Python, databases, and workflow orchestration tools. Mention any experience with containerisation and CI/CD practices. We love seeing concrete examples of your work, so don’t hold back!
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 shows us you’re keen to join our team!
How to prepare for a job interview at CuspAI
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals, especially around data pipelines and large-scale data processing. Be ready to discuss your experience with Python, databases, and workflow orchestration tools like Airflow or Prefect. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Show Your Collaborative Spirit
Since this role involves working closely with scientists and ML researchers, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve integrated diverse data sources or partnered with cross-functional teams to achieve a common goal.
✨Demonstrate Your Problem-Solving Skills
Think of specific challenges you've faced in previous roles and how you overcame them. Whether it was ensuring data quality or building scalable systems, having concrete examples will help illustrate your ability to tackle complex problems, which is crucial for this position.
✨Express Your Passion for Science and Technology
Let your enthusiasm for materials science and the potential applications of technology shine through. Talk about why you’re excited about the opportunity to enable scientists and how you see your role contributing to meaningful advancements in the field. This personal connection can set you apart from other candidates.