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aqemia.com

Senior Data Engineer

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About AQEMIA

AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI, our proprietary molecule-invention platform, which uniquely combines cutting-edge science with advanced technology. Powered by physics-based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles.
What makes AQEMIA different is our commitment to true innovation: our research is dedicated to the invention of new molecular entities, not the refinement of existing ones. We focus on inventing never-before-seen molecules, without relying on experimental data, and advancing them into a growing pipeline of proprietary programs and strategic partnerships with leading pharmaceutical companies.
Our most advanced preclinical programs are currently in vivo optimization, targeting diseases still waiting for effective treatments, offering our teams the opportunity to work on science that can make a real difference in people’s lives.
For more information, visit AQEMIA.com, our WTTJ Page, and our LinkedIn.

About our Team

AQEMIA brings together a diverse, multidisciplinary team of 80+ professionals based in Paris and London. Our scientists and engineers, including chemists, physicists, machine learning experts, and software engineers, work side by side to push the boundaries of early-stage drug discovery.
This close collaboration across disciplines is central to our approach, enabling us to tackle complex scientific challenges from first principles and translate cutting-edge ideas into novel therapeutic candidates. At AQEMIA, team members are encouraged to contribute their expertise, learn from one another, and play an active role in shaping the future of drug invention.

About our Engineering Department

The Engineering team (~12 people) builds and scales the technical foundations that power Aqemia’s drug discovery engine.
Bringing together expertise across software engineering, cloud infrastructure, data engineering, site reliability engineering (SRE), and scientific computing, the team designs and operates robust, secure, and high-performance platforms that enable Aqemia’s scientific and AI teams to experiment, train, deploy, and run models at scale.
Their work spans data infrastructure, scientific compute systems, cloud operations, orchestration, observability, CI/CD, developer tooling, and platform scalability. By transforming cutting-edge research into reliable and scalable systems, the team accelerates the discovery of new medicines while ensuring operational excellence and an outstanding developer experience.

The Role

As a Senior Data Engineer, you will play a key role in designing, building, and evolving AQEMIA’s data platform. You will work at the intersection of software engineering, data infrastructure, machine learning, and scientific research, enabling teams across the company to access trusted, scalable, and high-quality data.

You will contribute to the architecture of our data ecosystem, build reliable data pipelines, improve data accessibility and observability, and help establish best practices that support AQEMIA’s growing scientific and business needs.

Much of what makes this role distinctive is the data itself: chemical structures, molecular conformations, physics and ML-based predictions, and experimental results from CROs and partners. A core part of the work is modelling these scientific entities well, establishing canonical identity, provenance, and trustworthy lineage across heterogeneous and often messy sources so that scientists, and increasingly AI solutions and agents, can rely on them.

This is an opportunity to work on complex and impactful data challenges in a unique environment where physics, AI, and drug discovery converge.



Responsibilities

  • 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 experimental and in-silico 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 running in cloud environments.

  • Collaborate closely with Software Engineering, AI, Product, and Scientific teams to translate complex requirements into scalable technical solutions.

  • Contribute to DataOps practices, including testing, deployment automation, operational excellence, and platform reliability.

  • Mentor and support other engineers through technical guidance, knowledge sharing, and engineering best practices.

  • Participate in architecture discussions, technical planning, and long-term platform evolution initiatives.

    • Qualifications

  • 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. As AI tooling takes over more of the routine side of engineering, deep understanding of what the data means is increasingly what differentiates great work, so curiosity here matters as much as raw engineering speed.

  • 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.

  • Hands-on experience with Snowflake, dbt, and a workflow orchestrator such as Airflow.

  • Familiarity with DataOps practices, including observability, testing, monitoring, and deployment automation.

  • Experience collaborating with cross-functional stakeholders to deliver reliable and scalable data solutions.

  • Strong problem-solving skills and ability to navigate complex technical environments.

  • Excellent communication skills and ability to explain technical concepts to diverse audiences.

    • Nice-to-Have

  • Experience supporting machine learning, scientific computing, or research-oriented environments.

  • Experience with workflow orchestration platforms and event-driven data architectures.

  • Experience implementing data governance, lineage, and metadata management solutions.

  • Track record of improving platform scalability, reliability, and operational maturity.

  • Experience mentoring engineers or helping shape engineering best practices across teams.

    • Our Recruitment Process

    1. Talent Acquisition Interview (30 min)

    2. Hiring Manager Interview with Jonathan, Data Manager (45 min)

    3. Technical Assessment (60 min)

    4. VP Interview with Sylvain, VP Engineering (45 min)

    5. Culture Fit Interview with Emmanuelle Martiano, Co-founder & COO (45 min)

    6. Final Interview with Maximilien Levesque, Co-founder & CEO (60 min)

    Why Join Us?

    At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team.
    Expanding Drug Discovery Pipeline : Focused on critical therapeutic areas like Oncology, CNS, Immuno-inflammation... with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.
    World-Class Interdisciplinary Team : work alongside exceptional talent at the intersection of technology and life sciences. Our teams combine deep expertise in AI, physics-based modeling, biology, and medicinal chemistry to push the boundaries of innovation.
    DeepTech Recognition: AQEMIA is proud to be part of the French Tech 120 and France 2030, highlighting our role as a key player in Europe’s DeepTech ecosystem.
    Prime Location with Flexibility : Our offices are located in the heart of Paris and London (King’s Cross), with flexible work arrangements including up to two remote days per week.
    Strong Financial Backing : $100M raised from leading European and International investors