Principal Platform Engineer - Research Data Platform

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. 

About Lilly 

At Lilly, everything we do starts with patients. We unite caring with discovery to make life better for people around the world. Headquartered in Indianapolis, Indiana, our global team of over 50,000 employees work with urgency and purpose to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. We bring our best to this work because people depend on it. If you're driven by purpose and determined to make a meaningful difference for patients, we invite you to bring your skill and your commitment to Lilly.  

About Technology@Lilly 

At Lilly, technology is not a support function. It is how a global medicine company operates, innovates, and delivers. Lilly in Bengaluru builds the capabilities that make this possible, cloud platforms, AI systems, and automation at enterprise scale, all in service of a purpose that makes this technology work genuinely distinctive, from advancing drug discovery to enabling connected clinical trials to keeping a global medicine company running at the standard patients deserve.  

About the Business Function  

The Software Product Engineering (SPE) team is a specialized engineering group that delivers strategic solutions and differentiated capabilities. We take a forward-thinking approach, focusing on an enterprise platform and product mindset, ensuring that the solutions we build can be leveraged across Technology teams for broader impact and efficiency.  

What You'll Do 

DevOps and Infrastructure 

• Own and evolve the platform's delivery and runtime foundations across CI/CD, infrastructure-as-code, Kubernetes/EKS, and AWS services - ensuring platform components can be built, deployed, scaled, and rolled back safely.  

• Design and maintain reliable deployment workflows using Jenkins, GitHub Actions, container registries, environment promotion strategies, and automated validation gates for application and data-platform services.  

• Strengthen operational excellence through observability, logging, metrics, alerting, runbooks, and incident-response practices that improve service reliability, recoverability, and mean time to resolution.  

AI, Agents and MCP Tooling  

• Design and build AI agents and intelligent automation tools that help research scientists and data engineers interact with the platform more effectively.  

• Design and implement MCP (Model Context Protocol) integrations that connect AI agents to platform data sources, tools, and services - enabling seamless, tool-augmented workflows for end users.  

• Evaluate and integrate emerging AI tools, frameworks, and patterns into the platform's development workflows - finding opportunities where AI-assisted development, code generation, or intelligent automation can meaningfully accelerate the team's delivery. 

Data Engineering and Platform Capabilities 

• Bring enough familiarity with modern data-platform patterns to collaborate effectively with data engineering teams - including Airflow, Glue/Spark, Kafka/MSK, and Lakehouse oriented architectures.  

• Apply platform engineering skills such as API design, service integration, automation, operational troubleshooting, and reusable tooling to strengthen the reliability and usability of data-platform capabilities.  

Crosscutting 

• Contribute to platform documentation, technical design proposals - ensuring that AI integrations, MCP patterns, and cross-cutting platform capabilities are well-documented and accessible.  

• Rotate into feature or platform squads as needed - this role is deliberately not siloed to a single domain.  

• Platform engineering mindset: able to design reusable tooling, APIs, service integrations, self-service workflows, and automation that improve developer and user productivity.  

Required Qualifications 

• Bachelor's or master's degree in computer science, Information Technology, or a related technical field - required.  

• 6-10 years of professional experience in DevOps, platform engineering, infrastructure engineering, with demonstrated ownership of production systems.  

• Strong hands-on Python proficiency for automation, APIs, AI tooling, scripting, operational workflows, and platform integrations.  

• Hands-on experience building, operating, and troubleshooting CI/CD pipelines using tools such as Jenkins, GitHub Actions, automated validation gates, and deployment promotion workflows.  

• Solid working knowledge of AWS, infrastructure-as-code, containerized workloads, and Kubernetes/EKS-based runtime environments.  

• Strong operational mindset across observability tools (such as Loki, Tempo or Grafana), logging, metrics, alerting, runbooks, incident response, root-cause analysis, and reliability improvement.  

• Practical curiosity or hands-on experience with LLMs, AI agents, MCP, tool integrations, or AI-assisted automation; production AI experience is helpful but not required.  

• Experience writing unit tests, integration tests, and automated test suites, with a bias toward building quality and validation into delivery workflows.  

• Proven track record to independently identify problems worth solving and deliver practical, maintainable solutions with minimal guidance.  

• Strong communication and customer fluency, with the ability to work across research scientists, data engineers, platform teams, and technical leadership.  

Nice to Have 

• Experience with workflow orchestration tools (Airflow preferred).  

• Familiarity with data transformation (DBT), distributed computing (Spark, Glue), data lakehouse concepts (Iceberg), or data quality frameworks (Great Expectations).  

• Streaming technologies (Kafka, MSK) - understanding of event-driven architectures.  

• Trino or similar distributed query engines.  

• Java - ability to read, understand, and contribute to existing Java-based platform services.  

• AWS certifications (Cloud Practitioner, AI Practitioner, or higher).  

At Lilly, caring is not only what we do for patients, it is how we work. We believe the people who dedicate themselves to making medicines better deserve an environment that makes their lives better too, one where they are supported, respected, and given the space to do their best work. This is not just a policy; it is who we are.  

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.