Senior Data Engineer

Aqemia.com

Location

Paris

Job Type

Full-time

Posted

September 23, 2026

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Job Description

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

7-10 years of experience in Data Engineering, ideally in fast-paced technology, scientific, AI or data-intensive environments.

Strong software and data engineering skills — able to code, with deep experience in data modeling and relational databases.

Strong proficiency in Python and SQL, with experience building and maintaining production-grade data systems.

Hands-on experience with dbt, Airflow, or similar modern data stack tooling.

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

First discussion with our Talent Acquisition
Hiring Manager’s interview: you’ll meet directly with your future manager
Technical assessment of your skills in a deep-dive interview with the team
VP interview to share wider team vision and align motivations
Cultural fit interview with our co-founder and COO, Emmanuelle
Final interview with our co-founder and CEO, Maximillien

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?

The job is located in Paris at Aqemia.com. The posting does not specify a remote, hybrid, or on-site work-mode policy.

What are the key responsibilities for this role?

You will own end-to-end data pipelines, model scientific entities, set data quality standards, partner with ML and research teams, drive data architecture, build self-service APIs, and mentor junior engineers.

What qualifications and experience do I need to apply?

You need 7-10 years of data engineering experience, strong Python and SQL skills, deep experience in data modeling and relational databases, hands-on experience with dbt or Airflow, and a STEM degree or equivalent experience.

Who will I report to or work with?

You will work as a senior individual contributor, collaborating with the Engineering Manager and Staff Data Engineer on roadmap execution, and partnering with ML engineers, data scientists, and researchers.

What is the recruitment process for this position?

The process consists of six steps: a Talent Acquisition discussion, a Hiring Manager interview, a technical assessment deep-dive, a VP interview, a cultural fit interview with the co-founder/COO, and a final interview with the co-founder/CEO.