Senior Data Engineer (AI)

Location: Paris or London; Workplace: Hybrid

Company

hirify.global develops scientific data and machine-learning capabilities around chemical structures, molecular predictions, and experimental research.

What you will do

• Own Bronze → Silver → Gold data pipelines from ingestion and transformation through delivery.
• Model canonical scientific entities such as compounds, structures, assays, predictions, and experimental results.
• Establish data provenance, lineage, validation, monitoring, testing, alerting, and governance standards.
• Partner with ML engineers, data scientists, and researchers to build curated, model-ready datasets.
• Shape data architecture, orchestration, documentation, deployment, self-service capabilities, and future APIs.
• Review code and mentor junior engineers as a senior individual contributor.

Requirements

• 7–10 years of experience in data engineering, preferably in technology, scientific, AI, or data-intensive environments.
• Strong software and data engineering skills with deep experience in data modelling and relational databases.
• Strong proficiency in Python and SQL, with experience building production-grade data systems.
• Hands-on experience with dbt, Airflow, or similar modern data-stack tools.
• STEM degree or equivalent experience.

Nice to have

• Experience with AWS, Terraform, modern data warehouses, object storage, or data governance solutions.
• Experience in drug discovery, biotech, pharma, or deeptech environments.
• Exposure to AI-driven or data-intensive workflows across biology, ML, and chemistry.
• Experience improving platform scalability, reliability, and operational maturity.

Culture & Benefits

• Hybrid work based in Paris or London.
• Close collaboration with engineering, ML, data science, and scientific research functions.
• Opportunity to shape architecture and service- and API-driven data integration.
• Knowledge sharing, code reviews, and mentoring within the engineering organization.

Hiring process

• Discussion with Talent Acquisition followed by a Hiring Manager interview.
• Technical deep-dive interview with the team.
• VP interview, cultural fit interview with the co-founder and COO, and final interview with the co-founder and CEO.