Senior Data Engineer

Aqemia; Paris; Hybrid; EUR 60,000 - 80,000; Full time

Benefits offered by this job

Flexible working arrangements

Strong financial backing

World-class interdisciplinary team

Job summary

Aqemia, based in Paris, is seeking a Senior Data Engineer to design and build scalable data pipelines that support scientific and operational workloads. This role involves contributing to the data platform architecture and collaborating across teams to ensure high-quality data access.

The ideal candidate has over 5 years of experience in Data Engineering, proficiency in Python and SQL, and is familiar with AWS and modern data tools. This position offers flexible working arrangements.

Qualifications

• 5+ years of experience in Data Engineering or related roles.
• Strong proficiency in Python and SQL.
• Experience in scalable data pipelines.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Contribute to evolution of data platform and architecture.
• Collaborate with teams to translate requirements into solutions.

Skills

Python

SQL

Data modeling

Distributed data systems

AWS

Snowflake

DataOps practices

Tools

Data orchestration tooling

Workflow orchestration platforms

Job description

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.

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.
• 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.
• Experience designing and operating scalable data pipelines and data platforms.
• Strong understanding of data modeling, distributed data systems, and modern data architecture principles.
• Experience with cloud environments, preferably AWS.
• Hands-on experience with Snowflake and modern data orchestration tooling.
• 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.
• Exposure to bioinformatics, computational chemistry, life sciences, or other scientific data domains.
• 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.

Benefits

• Expanding Drug Discovery Pipeline focused on critical therapeutic areas with in vivo proof of concept and patent stage programs, and collaborations with top Pharma.
• World-class interdisciplinary team combining AI, physics-based modeling, biology, and medicinal chemistry.
• DeepTech recognition as part of French Tech 120 and France 2030.
• Prime location in Paris and London (King’s Cross) with flexible working arrangements, including up to two remote days per week.
• Strong financial backing – $100M raised from leading European and International investors.