(Senior) Data Engineer (m/f/d)

Your role

As a Senior Data Engineer, you will own key parts of our data ecosystem and platform capabilities that enable advanced analytics, machine learning, and NLP/LLM applications. Your focus is to make data usable at scale: well-structured, traceable, governed, and accessible for downstream AI/ML use cases and enterprise applications. You will work closely with the materials experts, simulation teams, lab stakeholders, and AI/ML colleagues to translate product goals into robust data products and production-ready solutions.

Key responsibilities

• Design, implement, and operate scalable data pipelines for structured and unstructured data, including batch processing and event-driven or streaming workflows where needed.
• Develop cloud-native and on-premises architectures for data and AI workloads (primarily on Microsoft Azure).
• Build and evolve a materials data ecosystem linking physics-based modeling/simulation data and experimental laboratory data
• Handle large-scale scientific datasets (e.g., atomistic simulations, DFT/MD, high-throughput campaigns), including efficient storage, metadata, and performant access patterns
• Integrate data from HPC/simulation workflows and laboratory systems (instrument exports, LIMS/ELN where applicable) into curated, analysis-ready datasets
• Define and implement data models, metadata standards, and provenance to ensure traceability, reproducibility, and auditability across simulations and experiments
• Establish robust data quality practices (validation rules, unit consistency, schema controls) and data quality monitoring aligned with operational SLAs/SLOs
• Implement data governance foundations (cataloging, access control, lineage) and enable policy-driven data sharing across teams
• Work with the DevOps team to implement and improve CI/CD pipelines, deployment automation, and infrastructure requirements for data and AI workloads.
• Ensure reliability, security, GDPR compliance, monitoring/observability (logging, metrics, alerting), and cost efficiency of cloud platforms
• Provide technical leadership through design reviews, documentation of standards, and mentoring where appropriate

Your profileEducation & experience

• Degree in Computer Science, Data Science & Engineering, Mathematics, Natural Sciences, or a comparable field
• 3+ years of professional experience in data engineering.
• Experience designing or operating data ecosystems that unify multiple data domains with strong governance and provenance

Technical skills

• Strong Python skills and experience with data processing frameworks.
• Strong SQL skills and experience with data modeling for analytics and production use cases
• Familiarity with Vector databases, semantic search, text chunking strategies, LLM workflows and RAG architectures.