Principal Software Engineer

Boehringerprd; Buenos Aires; On-site; ARS 121,164,000 - 212,038,000; Full time

Job summary

Boehringer Ingelheim seeks a Data Platform Engineer to design, build, and operate cloud-native platform services on AWS and Snowflake. You will develop scalable data ingestion and processing solutions, implement event-driven architectures, and create reusable components and APIs to boost engineering productivity.

The role emphasizes automation, CI/CD, IaC, observability, and collaboration with data engineers, security, and business stakeholders to advance data and AI initiatives across the

Qualifications

• Strong hands-on experience designing and implementing cloud-native solutions on AWS and Snowflake.
• Proficiency in Java, Python and SQL, with production-grade software delivery.
• Experience with CI/CD pipelines, IaC, and observability tooling.
• Understanding of event-driven architectures and scalable integration patterns.

Responsibilities

• Design, build, and operate cloud-native platform services on AWS and Snowflake.
• Develop scalable software for data ingestion, processing, and consumption.
• Implement event-driven architectures and robust integration patterns.
• Build reusable platform components, APIs, and automation to improve productivity.
• Automate provisioning, deployment, monitoring, and operational processes.
• Contribute to platform architecture, standards, and engineering best practices.
• Develop CI/CD pipelines and Infrastructure-as-Code solutions.
• Implement observability, logging, and alerting across services.
• Collaborate with data engineers, security teams, and stakeholders to deliver platform solutions.
• Apply AI-assisted development practices to improve productivity and quality.

Skills

AWS

Snowflake

Java / Python

CI/CD

Kubernetes

APIs

Event-driven

IaC

Git

Tools

Jenkins

Docker

Kubernetes/OpenShift

dbt

Apache Airflow

Git

Job description

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.