Senior Data Engineer

I am collaborating with a very exciting, incredibly well backed, start up, Biotech company with offices in Amsterdam and Zurich

They are building a cutting-edge data platform and developing a multimodal foundation model that leverages complex datasets to improve cancer diagnosis, treatment, and patient outcomes. As part of their team, you'll be at the forefront of innovative technologies that help drive advancements in personalized medicine and cancer research.

They are looking for an experienced Senior Data Engineer to design, develop, and maintain a robust data infrastructure for their oncology-focused AI platform. You will play a key role in architecting and scaling a high-performance data platform that supports multimodal data processing, data lake architecture, and machine learning pipelines, all within a secure, scalable, and cloud-based environment.

Responsibilities

Architect, build, and maintain scalable data pipelines and infrastructure that support multimodal data for oncology AI models.
Develop and optimize data workflows for ingesting, transforming, and processing diverse oncology-related data (e.g., medical imaging, genomics, clinical data) using Apache Spark and Python.
Design and manage data storage, processing, and orchestration on Azure, ensuring reliability, security, and scalability.
Utilize Terraform to automate infrastructure provisioning and deployment, ensuring repeatability and reducing manual configurations.
Implement and manage Kubernetes clusters for deploying and managing data workflows and model training pipelines.
Work closely with data scientists, ML engineers, and product teams to understand data requirements and provide end-to-end support on data ingestion, transformation, and accessibility.
Monitor and fine-tune the data pipelines to improve efficiency, reduce latency, and optimize resource usage.
Document data pipeline architecture, transformations, and ensure adherence to industry standards and compliance requirements in healthcare data handling (e.g., HIPAA, GDPR).

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Extensive experience in data engineering with a focus on large-scale data processing and cloud platforms.
Proficiency in Python for data engineering tasks and scripting.
Strong experience with Apache Spark for ETL, batch, and stream processing.
Expertise in Microsoft Azure (Data Lake, Data Factory, Azure Databricks, etc.).
Hands-on experience with Terraform for managing cloud infrastructure.
Experience with Docker and Kubernetes for deploying scalable applications.
Experience with healthcare data, particularly in oncology, is a strong plus.
Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
Strong communication skills for cross-team collaboration and technical documentation.

Benefits

Comprehensive salary
Long term incentives
25+ days holiday
Clear development pathway

Following your application Joe Templeman, a specialist AI Recruiter will discuss the opportunity with you in detail.

He will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available.

This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.

Please click ‘apply’ or contact Joe Templeman for any further information
Joe Templeman
Recruitment Manager – Barrington James
Email: jtempleman (at) barringtonjames.com