Scientific Data Platform Engineer

Role Summary

Join Just-Evotec as a Scientific Data Platform Engineer in Seattle, WA. You will architect, build, and maintain scalable data platforms and pipelines across scientific and business domains, design data orchestration workflows, and integrate data from diverse laboratory sources. Collaborate with software engineers and scientists to ensure data systems meet performance, reliability, and usability standards, with a focus on data modeling, metadata management, and governance, while staying current with cloud and data engineering best practices.

Responsibilities

• Architect, build, and maintain scalable data platforms and pipelines to support operational and analytical data needs across scientific and business domains.
• Design and implement data orchestration workflows using modern tools and frameworks.
• Integrate data from diverse scientific and laboratory sources into centralized data systems and platforms.
• Collaborate with software engineers and scientists to ensure data systems meet performance, reliability, and usability standards.
• Lead efforts in data modeling, metadata management, and data governance.
• Stay current with emerging technologies and best practices in cloud computing, data engineering, and biotherapeutic data systems.
• Communicate technical concepts clearly and effectively to both technical and non-technical stakeholders.
• Draft technical documentation, architecture diagrams, and operational procedures.
• Spend at least 2 days a week at our Seattle site.

Qualifications

• Ph.D. in computer science, data engineering, physical sciences, or a related field with a strong data engineering focus and 4+ years of experience.
• Proven experience building and maintaining data pipelines and orchestration systems.
• Proficiency in Python and experience with version control systems and DevOps.
• Hands-on experience with AWS cloud services, including S3, Lambda, Fargate, and ECS.
• Familiarity with modern data architectures for operational and analytical systems (e.g., data lakes, lakehouses, event-driven architectures).
• Strong understanding of relational databases, SQL, and data exchange formats.

Skills

• Python programming
• AWS cloud services (S3, Lambda, Fargate, ECS)
• Data pipelines and orchestration systems
• Data modeling, metadata management, and data governance
• Relational databases and SQL
• Communication and collaboration with technical and non-technical stakeholders

Education

• Ph.D. in computer science, data engineering, physical sciences, or a related field

Additional Requirements

• Experience working with Laboratory Information Management Systems (LIMS) in a commercial setting.
• Experience in physical science domains (e.g., chemistry, biology).
• Familiarity with data science toolsets (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with scientific data visualization and dashboarding tools.
• Proficiency with additional programming languages such as Java or R.