High-Dimensional Biology Data Flow Orchestration Engineer

We are searching for the best talent for High-Dimensional Data Flow Orchestration Engineer, R&D Therapeutics Discovery in Spring House, PA or Beerse, Belgium.

The High-Dimensional Biology Data Flow Orchestration Engineer acts as the keystone of data flow automation projects for high-dimensional biology teams including, among others, Transcriptomics, Proteomics and High-Content Imaging. The candidate will ensure that scientific data is automatically transferred, processed and analyzed with minimal user intervention. This role requires strong expert-level capabilities in data flow automation, solution implementation, to deliver efficient, scalable, and compliant data flow automation solutions across modality agnostic Therapeutics Discovery.

What You’ll Do:

• Architect and deploy automated data pipelines for scientific workflows.
• Lead end-to-end projects from concept to production in a global, matrixed environment.
• Integrate advanced tools and platforms across cloud, on-prem, and container ecosystems.
• Collaborate with cross-functional teams and mentor/train computational biologists in the use of the infrastructure.
• Explore emerging technologies in AI/ML and automation to accelerate innovation.
• Ensure data quality, lineage, security, and compliance at scale.

What We’re Looking For:

• Degree in Computer Science, Data Engineering, or related field; advanced degree (MS/PhD) preferred.
• 5+ years building production-grade data platforms and automated workflows.
• Hands-on experience with workflow languages and orchestration tools (Nextflow, Argo, Airflow) and scalable compute environments (eg Kubernetes).
• Strong scripting and programming skills (Python, Bash, SQL), proficiency in cloud ecosystems (eg AWS) and distributed frameworks (Spark, Dask).
• Proven leadership in complex, multi-stakeholder projects.
• Strong analytical mindset, problem-solving agility, and a collaborative leadership style.
• Experience with domain‑specific pipelines (bioinformatics, genomics, imaging) or production ML platforms (model registries, feature stores).

Core Expertise

• Architecture & Design: Design scalable, resilient data flow architectures; create reusable pipeline templates and IaC modules (Terraform).
• Systems & Integration: Skilled in container orchestration (Kubernetes, Docker), CI/CD (GitHub Actions, GitLab CI), and workflow engines (Nextflow, Argo). Experienced with cloud storage (S3), data warehouses (Snowflake), and integration tools (Kafka, APIs, metadata catalogs).
• Leadership & Delivery: Lead cross-functional matrix teams, set roadmaps, manage vendors, and drive complex projects from concept to production.
• Communication: Translate technical trade-offs into business impact; produce clear documentation and onboarding guides.

Preferred Qualifications

• Industry exposure: Experience in pharmaceutical research, biotech, or medical device environments.
• Data governance: Strong understanding of data integrity, lineage, security frameworks, and scalable data architectures.
• Data Reliability & Observability: Implement automated data quality checks, lineage tracking, and schema evolution. Strong background in monitoring, metrics, and capacity planning.

Preferred Skills:

Accessible Design, Agility Jumps, Business Alignment, Cloud Computing, Cloud Migrations, Cloud Security, Coaching, Critical Thinking, Human-Computer Interaction (HCI), Hybrid Clouds, Multi Cloud Models, Organizing, Presentation Design, Software Development Life Cycle (SDLC), Software Development Management, Tactical Planning, Technical Credibility, Technical Writing

Hybrid Work