Senior Data Engineer

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 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 our Senior Data Engineer, you'll own AQEMIA's data platform end to end - from ingestion through the pipeline to the trusted, model-ready datasets that power science, ML and analytics. 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, often messy sources - so scientists, and increasingly AI agents, can rely on them. You'll work at the intersection of software engineering, data infrastructure and scientific research, with real scope to shape architecture rather than just execute against it.

As AQEMIA moves toward more service and API-driven integration next year, you'll help make data fit for automation, expanding your impact from pipelines to the systems that consume them.

Responsibilities

• Own AQEMIA's Bronze → Silver → Gold data pipelines end to end, from ingestion through transformation and delivery, maintaining lineage and traceability as data volume and complexity grow.

• Model canonical scientific entities, compounds, structures, assays, predictions, establishing identity, provenance and trustworthy lineage across heterogeneous and often messy sources.

• Set and uphold data quality standards through monitoring, validation, testing and alerting across critical pipelines, strengthening governance and observability so datasets stay trusted and accessible.

• Partner with ML engineers, data scientists and researchers to build curated, model-ready datasets, translating scientific and business requirements into scalable data solutions.

• Drive data architecture and engineering best practices, data modeling, testing, documentation, orchestration and deployment, in collaboration with the Engineering Manager and Staff Data Engineer on roadmap execution.

• Build self-service capabilities and, looking ahead, APIs that make data fit for automation as AQEMIA moves toward more service-based integration.

• Uphold engineering quality through code reviews, and mentor junior engineers by sharing knowledge and best practices as a senior individual contributor.

Qualifications

• Deep experience in data engineering, with a track record of production systems that other teams depend on. We care about what you have built, not the year count.

• Strong software engineering skills. You code, you review code, and you hold a quality bar.

• Expert in Python and SQL.

• Strong data modelling and relational database experience. You can defend an identity key.

• Production experience with a cloud warehouse (we use Snowflake) and a transformation framework (we use dbt).

• Experience with workflow orchestration (we use Airflow) and infrastructure-as-code (we use Terraform on AWS).

• Any STEM degree or equivalent experience.

Nice‑to‑Have

• Experience with AWS.

• Experience with infrastructure-as-code (Terraform) and modern data warehousing (e.g. Snowflake, BigQuery, Redshift) and object storage.

• Experience in drug discovery, biotech, pharma or deeptech environments.

• Exposure to AI-driven or data-intensive workflows, or experience working across disciplines (e.g. biology ↔ ML ↔ chemistry).

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

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

Our recruitment process

1. First discussion with our Talent Acquisition

2. Hiring Manager’s interview: you’ll meet directly with your future manager

3. Technical assessment of your skills in a deep-dive interview with the team

4. VP interview to share wider team vision and align motivations

5. Cultural fit interview with our co-founder and COO, Emmanuelle

6. Final interview with our co-founder and CEO, Maximillien

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 40 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.