Data Platform Engineer — Scale Scientific Data & ML

Aqemia; Paris; Híbrido; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

AQEMIA, based in Paris and London, is seeking a Senior Data Engineer to design, build, and evolve its data platform. You will enable cross-functional teams to access trusted, scalable data including chemical structures, ML predictions, and CRO results.

You will model entities, ensure data provenance, and foster DataOps practices while collaborating with software, AI, product, and science teams to advance drug discovery initiatives.

Formación

• 5+ years of experience in Data Engineering, Platform Engineering, or related infrastructure-focused roles.
• Strong proficiency in Python and SQL, with experience building and maintaining production-grade data systems.
• Demonstrable interest in, or experience with, scientific data domains such as computational chemistry, bioinformatics, or life sciences.
• Experience designing and operating scalable data pipelines and data platforms.
• Strong understanding of data modeling, analytical warehouse design, and modern data architecture principles.
• Experience with cloud environments, preferably AWS.

Responsabilidades

• Design, build, and maintain scalable data pipelines supporting scientific, machine learning, and operational workloads.
• Contribute to the evolution of AQEMIA’s data platform, architecture, and infrastructure.
• Develop reliable systems for data ingestion, transformation, storage, and distribution across multiple data sources.
• Model canonical scientific entities (compounds, structures, assays, predictions), establishing identity, provenance, and lineage across heterogeneous sources.
• Improve data quality, reliability, observability, and governance practices across the organization.
• Implement monitoring, validation, lineage, and documentation standards to ensure trust in data assets.
• Build self-service capabilities that enable scientists, engineers, and technical teams to discover and consume data efficiently.
• Optimize performance, scalability, and cost-efficiency of data infrastructure in the cloud.
• Collaborate with Software Engineering, AI, Product, and Scientific teams to translate requirements into scalable solutions.
• Contribute to DataOps practices, including testing, deployment automation, operational excellence, and platform reliability.
• Mentor and support other engineers through technical guidance and best practices.
• Participate in architecture discussions and long-term platform evolution initiatives.

Conocimientos

Python

SQL

Data pipelines

Data modeling

AWS

Herramientas

Snowflake

dbt

Airflow

Descripción del empleo

AQEMIA, based in Paris and London, is seeking a Senior Data Engineer to design, build, and evolve its data platform. You will enable cross-functional teams to access trusted, scalable data including chemical structures, ML predictions, and CRO results.

You will model entities, ensure data provenance, and foster DataOps practices while collaborating with software, AI, product, and science teams to advance drug discovery initiatives.