DataOps/Data Engineer

il y a 15 heures


Paris, France Hlx Life Sciences Temps plein

We are supporting a fast-growing precision diagnostics company leveraging single-cell transcriptomics and AI to better understand tumor heterogeneity and improve cancer care. Their platform combines advanced biology, algorithms, and molecular signatures to deliver clinically actionable insights. The company is well-funded and works closely with leading European and US research and clinical institutions as it scales toward clinical-grade diagnostics. The Mission As the company transitions from research-focused pipelines to clinical-grade production systems, robust and scalable data infrastructure is critical. We work with large, complex, multi-modal datasets, ranging from wet-lab outputs to clinical samples. These require high-performance pipelines, strong reproducibility, and secure cloud-based environments. As a Data Engineer, you will own the end-to-end data lifecycle, from raw biological data to clinically meaningful outputs, working closely with computational biologists, research scientists, and software engineers. Responsibilities Design, build, and optimize data pipelines for large-scale biological datasets (including single-cell data) Integrate and operate pipelines within a cloud-native AWS infrastructure Manage large datasets using workflow orchestration systems Collaborate with biologists and clinicians to support computational and analytical needs Ensure pipelines are robust, reproducible, monitored, and well-documented Test, maintain, and evolve production-grade codebases Experience 3+ years of experience as a Data Engineer or DevOps Engineer with strong coding practices Experience working on end-to-end pipelines in production environments Required Skills Hands-on experience with AWS and Infrastructure as Code (IaC) Experience designing, deploying, and monitoring scalable data workflows Strong proficiency in Python Solid engineering fundamentals and attention to detail Ability to collaborate effectively in multidisciplinary teams (engineering, biology, clinical) Nice to Have Experience with R Background or exposure to molecular biology, oncology, or bioinformatics Experience with databases (design, tuning, performance) Experience working in regulated or compliance-driven environments Working model Paris-based Hybrid setup (on-site collaboration + remote flexibility) #J-18808-Ljbffr


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