AWS DevOps Engineer

Machine Learning Reply offers customized end-to-end Data Science solutions covering the entire project life cycle from strategy consulting, data architecture and infrastructure to data processing with quality assurance using Machine Learning algorithms. The company has extensive expertise in Data Science across key industries of German HDAX companies, empowering clients to introduce data-driven business models and optimize existing processes with a focus on distributed open source and cloud technologies. It also provides a Machine Learning Incubator program to train future decision-makers, data scientists, and engineers.

• Degree in Computer Science, Information Systems, Data Analytics, or related field.
• 2.5+ years of experience in AWS Cloud, DevOps, or Cloud Engineering.
• Hands-on experience with Terraform and CI/CD pipelines in production environments.
• Strong understanding of AWS-native architecture and distributed systems.
• Experience managing production-grade cloud infrastructure and data pipelines.
• Ability to operate in complex, multi-account AWS environments.
• Experience with monitoring, incident response, and system reliability practices.
• Ability to work independently in ambiguous environments.
• Strong communication skills.
• Very good knowledge of English and Polish.
• Openness to visit office once every month.

• Take ownership of AWS multi-account environments.
• Design, build, and migrate CI/CD pipelines using GitHub Actions.
• Define and implement monitoring, logging, and alerting standards across systems.
• Collaborate with outgoing vendors to ensure smooth knowledge transfer.
• Support migration and refactoring of infrastructure into Terraform.
• Maintain and optimize cloud data pipelines and backend services.
• Analyze, validate, and document existing ETL pipelines and data flows.
• Ensure reliability, scalability, and security of AWS infrastructure.
• Participate in technical workshops on architecture and platform design.
• Work closely with data engineers, backend teams, and stakeholders.
• Utilize Tableau REST API for administration, automation, and operational improvements.

Openness to visit office at least once per month.