Research Data Specialist

Role purpose Lead and execute the management, integration, and architecture of biological data systems and computational infrastructure within the Bioinformatics group to support Seeds R&D in China. The role is responsible for structuring, storing, and governing diverse high-throughput biological experimental data, as well as managing analytical codebases across high-performance computing (HPC) clusters and modern cloud environments. Working closely with bioinformaticians, trait discovery scientists, functional genomics teams, and digital partners, the Research Data Specialist will optimize data flows, build scalable storage solutions, and ensure high-performance computing systems are robustly architected to accelerate data-driven crop biotechnology research. Accountabilities HPC & Cloud Platform Operations. Manage, configure, and optimize high-performance computing (HPC) cluster environments and cloud data warehouses to ensure seamless storage, retrieval, and analysis of large-scale biological datasets. Monitor system performance, compute resources, and data storage costs to optimize resource utilization. Biological Data & Code Lifecycle Management. Systematically manage, curate, and version biological experimental data (such as genomic, RNA-seq, data) along with accompanying bioinformatics software, scripts, and pipelines. Establish standardized code repositories, version control workflows, and documentation best practices for research teams. Pipeline Support & Integration. Partner closely with bioinformatics pipeline developers, data scientists, and experimental research teams to streamline data ingestion, preprocessing, and automated analysis workflows. Ensure raw data from multi-omics platforms and experimental assays are seamlessly transferred, validated, and formatted for analytical consumption. Cross-Functional Collaboration & Technical Training. Collaborate with local and global IT, AI Engineering, and Bioinformatics teams to align data storage and computing standards. Provide training and operational support to research scientists regarding data submission protocols, cloud usage, HPC Job Scheduling, and script versioning. Continuously evaluate emerging cloud storage solutions, distributed computing frameworks, and database architectures (e.g., Snowflake, AWS cloud-native services, graph databases) to modernize Syngenta’s biological data infrastructure and maintain technological edge. Knowledge, Experiences & Capabilities Knowledge : Strong knowledge of modern data storage, data warehousing, and cloud computing platforms (e.g., AWS S3/EC2, Snowflake, or equivalent enterprise systems). Deep familiarity with Linux/Unix operating systems, high-performance computing (HPC) cluster environments (e.g., Slurm, SGE), and job scheduling mechanics. Understanding of database systems (SQL) and data engineering workflows for managing structured and unstructured data. Basic understanding of popular high-throughput biological data types. Backgrounds of plant biology, biotechnology research, and biological experimental workflows is preferred. Education and Experience Ph.D. or Master’s degree in Bioinformatics, Computational Biology, Computer Science, Data Engineering, Information Technology, or a related quantitative discipline. 3+ years (for Ph.D.) or 5+ years (for Master’s) of experience in managing high-throughput data, HPC clusters, or enterprise cloud data architectures in academic or industry research environments. Proven track record of managing large-scale datasets, building data pipelines, and establishing code repository architectures. Demonstrated experience working on cloud infrastructure (Snowflake or equivalent platforms). Experience in agriculture, biotechnology, life sciences, or related research-intensive industries is preferred. Capabilities Proficiency in Python, Bash/Shell scripting, and SQL, with strong software development best practices (version control, containerization, documentation). Ability to architect, migrate, and optimize data workflows across HPC cluster servers and modern cloud platforms (AWS, Snowflake). Strong problem-solving skills with a focus on data governance, data integrity, and reproducible computational research. Ability to communicate complex technical, cloud, and computational infrastructure concepts effectively to experimental scientists and non-technical stakeholders. Demonstrated ability to establish productive cross-functional collaborations across bioinformatics, software engineering, and laboratory teams. Excellent written and spoken English Note : Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status. To learn more visit: Syngenta Seeds is one of the world’s largest developers and producers of seed for farmers, commercial growers, retailers and small seed companies. Syngenta seeds improve the quality and yield of crops. High-quality seeds ensure better and more productive crops, which is why farmers invest in them. Advanced seeds help mitigate risks such as disease and drought and allow farmers to grow food using less land, less water and fewer inputs. Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions.