AWS DevOps Engineer

Machine Learning Reply offers customized end-to-end Data Science solutions, covering the entire project life cycle – from initial strategy consulting, data architecture and infrastructure topics, to processing data with quality assurance using Machine Learning algorithms. Machine Learning Reply has extensive expertise in the field of Data Science in all key industries of German HDAX companies.

Machine Learning Reply empowers clients to successfully introduce new data-driven business models and to optimize existing processes and products – with a focus on distributed open source and cloud technologies. With the Machine Learning Incubator, the company offers a program to train the next generation of 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 roles.
• 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.