Principal Software Engineer

The Position At Boehringer Ingelheim, data is a key enabler of innovation, scientific advancement, and business transformation. Our global Data Platforms team builds and operates the cloud-based foundations that allow thousands of users, applications, and data products to securely exchange, process, and consume data at scale.

As a Data Platform Engineer, you will help design, build, and evolve modern cloud-native platform capabilities that power our enterprise data ecosystem. Working with AWS, Snowflake, event-driven architectures, modern software engineering practices, and AI-enabled development tools, you will contribute to creating scalable, resilient, and highly automated solutions used across the entire organization.

This role offers the opportunity to combine cloud engineering, software development, automation, and platform operations while working on strategic initiatives that directly influence the future of data and AI at Boehringer Ingelheim. Tasks and responsibilities Design, build, and operate cloud-native platform services and capabilities on AWS and Snowflake.

Develop scalable and maintainable software solutions that enable data ingestion, integration, processing, and consumption. Design and implement event-driven architectures using cloud-native messaging and integration services. Build reusable platform components, APIs, frameworks, and accelerators that improve engineering productivity.

Automate platform provisioning, deployment, monitoring, and operational processes. Contribute to platform architecture, technical standards, and engineering best practices. Develop and maintain CI/CD pipelines and Infrastructure-as-Code solutions. Implement observability, monitoring, logging, and alerting capabilities across platform services.

Collaborate with data engineers, architects, security teams, and business stakeholders to deliver platform solutions. Apply AI-assisted development practices to improve engineering productivity, code quality, testing, and automation. Troubleshoot and resolve platform, integration, and operational issues. Continuously improve platform reliability, scalability, security, and developer experience.

Requirements

Cloud Engineering Strong hands-on experience designing and implementing cloud-native solutions on AWS and Snowflake. Experience with: AWS Lambda, API Gateway, ECS, SQS, SNS, IAM Roles and Policies, CloudWatch. Strong understanding of cloud networking, security, resiliency, and scalability principles. Experience designing highly available and distributed cloud architectures.

Software Engineering Strong software engineering background with experience building production-grade applications and services. Proficiency in Java, Python and SQL. Experience with: Git, Code Reviews, Unit Testing, Automated Testing and Software Design Patterns. Ability to write clean, maintainable, and well-structured code.

Event-Driven Architecture & Integration Proven experience implementing event-driven solutions in cloud environments. Strong understanding of event orchestration, asynchronous processing, message-driven architectures, event streaming patterns. Experience designing loosely coupled and scalable integration solutions. Understanding of modern integration and API-based architectures.

DevOps & Platform Automation Experience implementing CI/CD pipelines and deployment automation. Hands-on experience with: Jenkins, Docker, Kubernetes/OpenShift Experience with Infrastructure as Code and automated platform management. Experience implementing monitoring, observability, and operational automation. AI-Enabled Engineering Experience using AI-assisted development tools and practices to improve software delivery.

Familiarity with: GitHub Copilot, AI-assisted testing and code generation, Automated documentation generation, AI-supported development workflows Interest in applying GenAI technologies to improve platform engineering and developer productivity. Data Platform Technologies Experience with data platforms and modern data architectures.

Familiarity with: Snowflake, dbt, Apache Airflow. Understanding of data processing, data integration, and data lifecycle concepts. Personal Skills Strong problem-solving and analytical mindset. Passion for engineering excellence, automation, and innovation. Ownership mentality with a focus on delivering reliable and scalable solutions.

Excellent collaboration and communication skills. Ability to work effectively in cross-functional and globally distributed teams. Continuous learning mindset and enthusiasm for emerging cloud and AI technologies. Fluent English, written and spoken. <div