At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

This role will be responsible for designing and building robust data pipelines, managing big data infrastructure, and supporting AI-driven initiatives within Lilly China.
AI Data Pipelines: Design and construct data pipelines specifically tailored for AI workflows. Automate the extraction, transformation, and loading (ETL) of large datasets. Implement real-time data processing for immediate analysis and decision-making. Machine Learning Model Deployment: Collaborate with machine learning teams to transition models from development to production. Optimize data architecture to support high-performance model inference. Monitor and maintain model performance post-deployment. Unstructured Data Management: Develop systems to ingest, clean, and structure data from varied unstructured sources. Apply techniques like natural language processing (NLP) to extract insights from text, audio, and images. Ensure the seamless integration of unstructured data into the overall data strategy. Data Quality Assurance: Establish data validation frameworks to guarantee the accuracy of datasets. Create data anomaly detection systems to identify and rectify data issues. Maintain data lineage and metadata management for traceability and auditability. Innovation and Research: Investigate new data technologies and AI tools to enhance data capabilities. Conduct performance benchmarking and implement improvements to data systems. Stay informed about industry trends and advancements in AI and data engineering.
Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• At least 5 years of experience in data engineering, including experience of handling of AI and non-structured data (e.g. documents, script, image, voice etc.)
• Experience with non-relational data stores (vector databases, graph databases, key-value stores, column-family databases).Experience with vector databases for tasks such as document retrieval and semantic search
• Experience with data pipeline and workflow management tools (e.g., Azkaban, Luigi, Airflow).
• Strong programming skills in languages such as Python, Java, or Scala.
• Experience working with unstructured data sources and implementing complex data processing workflows.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Strong communication skills in English and Mandarin, with the ability to engage effectively with both technical and non-technical stakeholders.

Preferred Qualifications:

• Master’s degree or higher in a relevant field.
• Experience with cloud services (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Contributions to open-source projects or publications in relevant technical fields.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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