Advisor - Informatics & Science Applications Architect

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.

**Company Overview**:
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 39,000 employees around the world work to discover and bring life-changing medicines to those who need them the most, 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.

LRL Tech unites science with technology to accelerate the Research and Development of medicines and to deliver therapeutic innovations. The team leverages technology and platforms to streamline scientific experimentation to help Researchers follow the science, to understand the disease and identify potential therapies. They are at the forefront of advanced analytics to enable data driven drug discovery, to innovate so Scientists can rapidly analyze and accelerate the discovery of new medicines.

**Position Overview**:
Key Responsibilities:
Architectural Leadership:

- Architect and build a multi-tenant, serverless informatics platform leveraging AWS Lambda, DynamoDB, S3, EBS, EFS, Route 53, and API Gateway.
- Design data partitioning strategies for multi-tenant scientific data storage and explore microservices frameworks for scalable architecture.
- Build scalable Research Data Lakes, asset registries, and metadata catalog to support large-scale scientific data ingestion and retrieval.

Complex Scientific Data Flow & Interoperability:

- Architect frameworks that facilitate seamless data exchange between discovery research systems, including LIMS, ELN, analytical tools, and registration systems.
- Implement RESTful and GraphQL APIs for high-performance data interoperability across computational models, bioassays, and experimental workflows.
- Establish scientific data standards to ensure consistency, traceability, and governance across the R&D landscape.

Scientific Workflow Automation & Computational Frameworks:

- Architect scientific workflow automation platforms using Apache Airflow, EventBridge, RabbitMQ, and Kafka, enabling real-time data acquisition and bioassay processing.
- Design platforms supporting in silico modeling, AI-driven analytics, and high-throughput screening simulations.
- Integrate Cloud (AWS/Azure) platforms with HPC clusters to handle bioinformatics, cheminformatics, and translational modeling workloads.

Cloud, DevOps, and Observability:

- Maintain deep technical hands-on expertise with AWS CloudFormation, Ansible, Jenkins, Git, and other DevOps automation tools.
- Implement observability solutions using Prometheus, Grafana, OpenTelemetry to monitor system health, performance, and workflows.
- Continuously learn, explore, and drive adoption of cutting-edge cloud-native, containerization, serverless, and scientific informatics trends.

Cross-Functional Scientific Collaboration:

- Collaborate closely with scientists, data scientists, computational biologists, formulation teams, and manufacturing engineers to co-create informatics solutions.
- Serve as a trusted technical advisor for cloud migration, scientific data modernization, and AI/ML integration projects.
- Work with UI/UX teams to create intuitive digital interfaces for scientific workflow automation and data exploration.

Technology Strategy, Governance & Best Practices:

- Drive architectural strategy, making informed decisions around buy vs. build, third-party integrations, and platform extensibility.
- Define and enforce best practices for scientific IT security, data privacy, compliance (GxP, FAIR), and cloud operations.
- Champion a modular, service-oriented, event-driven architecture to enable rapid innovation, maintainability, and scalability.

Required Qualifications:

- Experience:

- 10+ years of enterprise IT and scientific informatics architecture experience.
- Deep technical leadership experience in AWS serverless and scientific data integration projects.
- Proven experience building cloud-native, scalable platforms integrating LIMS, ELN, MES, compound registries, and scientific analysis tools.
- Education:

- Bachelor’s or Master’s degree in Computer Science, Bioinformatics, Information Systems, or related disciplines.
- Technical Expertise:

- Expertise in AWS serverless architectures (Lambd