5 Data Engineer Jobs Remote

ADMET Data Pipeline Development: Design, build and maintain scalable pipelines for ingesting, processing, and harmonizing diverse ADMET datasets from public sources (e.g., ChEMBL, PubChem) and proprietary assays., Data Harmonization: Standardize heterogeneous ADMET data formats (e.g., in vitro assays, in silico predictions) across network participants to enable modelling readiness of the data, Model-Ready Dataset Curation: Preprocess raw ADMET data (e.g., normalizing units, handling missing values) to support AI/ML model training for a variety of endpoints (like bioavailability, hERG inhibition, or CYP450 interactions), Data Quality Assurance: Implement and automate validation checks to ensure ADMET data integrity, Cross-Functional Integration: Work with computational chemists to optimize data structures for AI-driven ADMET models (e.g., graph-based representations for metabolic pathways), Work with our customers and potentially academic partners to define data preprocessing, selection, and benchmarking strategies for novel training tasks involving ADMET data, including leveraging and harmonizing assay data from different sources., Collaborate cross-functionally to ensure data and resulting models address real-world drug discovery needs., Mentor and guide team members on a content level, supporting the planning and breakdown of complex ADMET data preparation., Influence strategic decisions on data infrastructure and data quality assurance, Contribute to publications or open-source contributions where relevant.

Optimize end-to-end data pipeline performance, Develop and maintain scalable data processing solutions and backends, Integrate data sources using modern ETL/ELT practices, Clean and transform raw data using dbt, Build and maintain robust data quality frameworks and validation processes, Maintain and troubleshoot data architecture and infrastructure, Design, enhance, and maintain data processes and security best practices, Support ML & AI Engineers in building efficient data pipelines, Contribute to AI-driven applications

Develop & Optimize Data Pipelines, Enable Better Decision-Making, Ensure Data Quality & Governance, Collaborate Across Teams

Unterstützung bei der Implementierung von robusten und skalierbaren Datenpipelines, Unterstützung bei der Optimierung unserer Dateninfrastruktur in der Cloud (z.B. Kubernetes-Cluster), Automatisierung von Deployments und Schaffung von zuverlässigen Monitoring- und Alerting-Lösungen, Unterstützung beim Einrichten von Monitoring-Tools (z.B. Prometheus, Grafana), Optimierung von Schnittstellen und Cloud-Architektur

Support in developing cloud-based data pipelines, Maintain, develop and optimize data pipelines, Develop new features for our data pipeline, Optimize workflows and data structures

Create Smart Solutions: Entwickle KI- und Machine-Learning-Modelle, die Industrieprojekte in der Energiewende revolutionieren – von Predictive Analytics bis hin zur intelligenten Prozessautomatisierung., Dive Deep Into Data: Arbeite mit großen Datensätzen, erkenne Muster und entwickle präzise Vorhersagen, um die Performance unserer Kundenprojekte nachhaltig zu optimieren., Build the Future Infrastructure: Erstelle skalierbare Datenpipelines und state-of-the-art Cloud-Architekturen, um nahtlos große Datenmengen zu erfassen, zu analysieren und zu nutzen., Continuous Improvement: Überwache, optimiere und tune deine Modelle kontinuierlich, integriere Feedback und sorge dafür, dass wir immer am Puls der neuesten KI-Trends bleiben.