Data Engineer

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. Your main focus will be to build the pipeline infrastructure and tooling for data ingestion, moving towards self-serve setup for the scientific team members.

What you'll do

• 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.
• Build scalable systems to handle high-throughput computational chemistry calculations and experimental data.
• Partner closely with scientists to implement frameworks to automate quality checks for crystal structure data, chemical compositions, and experimental measurements.
• Build monitoring systems to ensure data integrity across all pipelines.
• Work hand in hand with ML researchers to understand data requirements for model training and inference.

What you'll need

• At least 3+ years experience in data engineering roles, preferably in scientific or research environments.
• High level of proficiency in Python and databases with experience in large-scale data processing.
• Advanced user of workflow orchestration tools (e.g. Airflow, Prefect, Dagster, Flyte or similar).
• Solid experience with containerisation (Docker, Kubernetes) and CI/CD practices.
• Direct experience handling large/complex datasets and interest in working with scientific packages.
• Experience designing systems that scale with growing data volumes and user demands.

Nice to have

• Experience with data from scientific computing (simulations or experiments).
• Knowledge of machine learning data requirements and MLOps practices.
• Academic background in Materials Science, Chemistry, Chemical Engineering, or related field.
• Understanding of crystallography, materials properties, and computational chemistry concepts.

What they offer

• Competitive salary and equity in CuspAI
• 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
• 26 weeks parental leave (primary caregiver) and 12 weeks (secondary caregiver) at full pay
• Professional development budget
• Work on meaningful problems advancing materials science and solving sustainability challenges