Senior Data Engineer

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

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.

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