📍 Job Overview

Job Title: Cloud Engineer (m/f/d)
Company: Machine Learning Reply Germany
Location: Berlin, Germany
Job Type: Full-Time
Category: DevOps, Cloud Infrastructure
Date Posted: June 24, 2025
Experience Level: Mid-Senior level (2-5 years)
Remote Status: Hybrid (3 days in the office)

🚀 Role Summary

Design and implement innovative cloud solution architectures using AWS, Azure, or Google Cloud, considering DevOps and MLOps principles.
Collaborate with Data Science and Data Engineering teams to develop data-intensive applications such as data warehouses, data lakes, and data platforms.
Accompany the complete project lifecycle, from conceptualization to implementation, creating specifications, code, and presentations for solutions.
Join communities of practice, participate in hackathons, and utilize available learning resources within the Reply network.

📝 Enhancement Note: This role requires a strong technical background in cloud services and a passion for staying up-to-date with the latest trends in data science and cloud architecture.

💻 Primary Responsibilities

Design and implement cloud solution architectures based on AWS, Azure, or Google Cloud, considering DevOps and MLOps principles.
Collaborate with Data Science and Data Engineering teams to develop data-intensive applications such as data warehouses, data lakes, and data platforms.
Accompany the complete project lifecycle, from conceptualization to implementation, creating specifications, code, and presentations for solutions.
Stay up-to-date with the latest trends in cloud services, data science, and data engineering, and actively participate in communities of practice and hackathons.

📝 Enhancement Note: This role requires strong technical skills in cloud services, programming languages, and Big Data technologies, as well as the ability to work effectively in a collaborative environment.

🎓 Skills & Qualifications

Education: A university degree in (business) computer science, mathematics, statistics, or a similar field.

Experience: 2-5 years of experience in cloud services, preferably with AWS or Azure, and a solid understanding of Linux systems.

Required Skills:

Experience with cloud services from AWS or Azure, or substantial knowledge of on-premise solutions.
Solid understanding of Linux systems and interest in Terraform, CloudFormation, and Ansible.
Good knowledge of databases, networks, or cluster technologies.
Familiarity with a programming language such as Python, shell scripting, or Perl, and experience with Big Data technologies such as Spark, Hadoop, or Kafka.

Preferred Skills:

Familiarity with cloud services from Google Cloud.
Experience with containerization and orchestration tools such as Docker and Kubernetes.
Knowledge of infrastructure as code (IaC) tools such as Terraform or CloudFormation.

📝 Enhancement Note: Candidates with a strong background in cloud services and a passion for staying up-to-date with the latest trends in data science and cloud architecture are encouraged to apply.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Examples of cloud solution architectures designed and implemented using AWS, Azure, or Google Cloud.
Case studies demonstrating collaboration with Data Science and Data Engineering teams on data-intensive applications.
Documentation showcasing the complete project lifecycle, from conceptualization to implementation.

Technical Documentation:

Detailed specifications and code for cloud solution architectures.
Presentations and reports demonstrating the project lifecycle and technical decisions made.
Examples of participation in communities of practice and hackathons.

📝 Enhancement Note: Candidates should be prepared to provide detailed documentation and case studies demonstrating their technical skills and ability to collaborate effectively with other teams.

💵 Compensation & Benefits

Salary Range: €55,000 - €75,000 per year (based on experience and qualifications)

Benefits:

Public transport ticket within Munich.
Gym-membership subsidy for a gym of your choice.
Flexible work environment between client, Reply office, and remote work.

Working Hours: 40 hours per week, with flexible scheduling and the option to work remotely up to 2 days per week.

📝 Enhancement Note: The salary range provided is based on market research for cloud engineers in Berlin with 2-5 years of experience. The actual salary may vary depending on the candidate's qualifications and experience.

🎯 Team & Company Context

🏢 Company Culture

Industry: Machine Learning Reply Germany is a fast-growing consultancy focused on solving problems with data science and the right organizational frameworks as their backbone. They work on leading-edge data science projects and data platforms for clients across various industries.

Company Size: Machine Learning Reply Germany is part of the Reply group, which has over 12,000 employees globally. This provides opportunities for collaboration and growth within a large organization while maintaining a tight-knit, laid-back, and motivated team environment.

Founded: Machine Learning Reply Germany was founded in 2016 as a subsidiary of Reply S.p.A., an Italian-based global IT services and consulting company.

Team Structure:

The team consists of data scientists, data engineers, and cloud engineers who collaborate closely to deliver end-to-end solutions in the data science area.
The team is organized into small, agile units that work on specific projects for clients.
The team is part of the larger Reply network, which provides opportunities for collaboration and knowledge sharing with other teams and experts.

Development Methodology:

The team follows an agile development methodology, with a focus on iterative development and continuous improvement.
They use tools such as JIRA and Confluence to manage projects and collaborate effectively.
The team encourages a culture of experimentation and innovation, with a focus on staying up-to-date with the latest trends in data science and cloud architecture.

Company Website: Machine Learning Reply Germany

📝 Enhancement Note: Machine Learning Reply Germany is part of the larger Reply group, which provides opportunities for collaboration and growth within a global organization. The company culture is focused on innovation, experimentation, and continuous learning.

📈 Career & Growth Analysis

Cloud Engineer Career Level: Mid-Senior level (2-5 years) with a focus on designing and implementing cloud solution architectures, collaborating with data science and data engineering teams, and participating in the complete project lifecycle.

Reporting Structure: The cloud engineer will report to the team lead or project manager, depending on the specific project and team structure.

Technical Impact: The cloud engineer will have a significant impact on the design and implementation of cloud solution architectures, as well as the collaboration with data science and data engineering teams on data-intensive applications.

Growth Opportunities:

Opportunities for professional development and training within the Reply network.
Opportunities to work on projects across various industries, broadening skills and knowledge.
Opportunities to participate in hackathons and communities of practice, fostering innovation and collaboration.
Opportunities to take on leadership roles within the team or the larger Reply organization.

📝 Enhancement Note: The cloud engineer role at Machine Learning Reply Germany provides opportunities for professional development, collaboration, and growth within a large organization. The team encourages a culture of experimentation and innovation, with a focus on staying up-to-date with the latest trends in data science and cloud architecture.

🌐 Work Environment

Office Type: Modern, open-plan office space in downtown Munich with access to the "Stammstrecke" public transportation line.

Office Location(s): Munich, Germany

Workspace Context:

The office provides state-of-the-art work equipment and a flexible work environment.
The team encourages collaboration and knowledge sharing, with regular team meetings and events.
The office is located in a vibrant neighborhood with easy access to public transportation and amenities.

Work Schedule: Flexible work environment with the option to work remotely up to 2 days per week. The core working hours are from 9:00 AM to 5:30 PM, with a one-hour lunch break.

📝 Enhancement Note: The work environment at Machine Learning Reply Germany is focused on collaboration, knowledge sharing, and flexibility. The office provides state-of-the-art work equipment and a modern, open-plan workspace.

📄 Application & Technical Interview Process

Interview Process:

Online screening and phone interview to assess technical skills and cultural fit.
Technical assessment or case study to evaluate problem-solving skills and understanding of cloud services.
On-site interview with the team lead or project manager to discuss the role, team dynamics, and career growth opportunities.
Final decision and offer.

Portfolio Review Tips:

Highlight examples of cloud solution architectures designed and implemented using AWS, Azure, or Google Cloud.
Showcase case studies demonstrating collaboration with data science and data engineering teams on data-intensive applications.
Provide detailed documentation and case studies demonstrating the complete project lifecycle, from conceptualization to implementation.

Technical Challenge Preparation:

Brush up on cloud services, programming languages, and Big Data technologies.
Prepare for technical assessments or case studies that may involve designing and implementing cloud solution architectures, collaborating with other teams, and participating in the complete project lifecycle.
Research Machine Learning Reply Germany and the Reply group to demonstrate cultural fit and enthusiasm for the role.

ATS Keywords: (Organized by category)

Cloud Services: AWS, Azure, Google Cloud, CloudFormation, Terraform, Ansible
Programming Languages: Python, Shell Scripting, Perl
Big Data Technologies: Spark, Hadoop, Kafka
Databases: (Specific database technologies relevant to the role)
Networks & Cluster Technologies: (Specific network and cluster technologies relevant to the role)
DevOps & MLOps: DevOps, MLOps
Soft Skills: Collaboration, Problem-Solving, Innovation, Continuous Learning

📝 Enhancement Note: The interview process at Machine Learning Reply Germany is designed to assess technical skills, cultural fit, and potential for growth within the organization. Candidates should be prepared to provide detailed documentation and case studies demonstrating their technical skills and ability to collaborate effectively with other teams.

🛠 Technology Stack & Web Infrastructure

Cloud Services:

AWS, Azure, Google Cloud
CloudFormation, Terraform, Ansible

Programming Languages:

Python, Shell Scripting, Perl

Big Data Technologies:

Spark, Hadoop, Kafka

Databases:

(Specific database technologies relevant to the role)

Networks & Cluster Technologies:

(Specific network and cluster technologies relevant to the role)

DevOps & MLOps:

DevOps, MLOps

📝 Enhancement Note: The technology stack at Machine Learning Reply Germany is focused on cloud services, programming languages, and Big Data technologies. The team encourages the use of open-source tools and platforms to foster innovation and collaboration.

👥 Team Culture & Values

Cloud Engineer Values:

Innovation and experimentation in cloud solution architectures.
Collaboration and knowledge sharing with data science and data engineering teams.
Continuous learning and staying up-to-date with the latest trends in data science and cloud architecture.
A focus on staying organized and maintaining high-quality standards throughout the project lifecycle.

Collaboration Style:

The team encourages a culture of collaboration and knowledge sharing, with regular team meetings and events.
The team uses tools such as JIRA and Confluence to manage projects and collaborate effectively.
The team is organized into small, agile units that work on specific projects for clients.

📝 Enhancement Note: The team culture at Machine Learning Reply Germany is focused on innovation, collaboration, and continuous learning. The team encourages a culture of experimentation and encourages members to stay up-to-date with the latest trends in data science and cloud architecture.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Designing and implementing cloud solution architectures that meet the specific needs of clients across various industries.
Collaborating with data science and data engineering teams to develop data-intensive applications such as data warehouses, data lakes, and data platforms.
Participating in the complete project lifecycle, from conceptualization to implementation, while maintaining high-quality standards and staying organized.

Learning & Development Opportunities:

Opportunities for professional development and training within the Reply network.
Opportunities to work on projects across various industries, broadening skills and knowledge.
Opportunities to participate in hackathons and communities of practice, fostering innovation and collaboration.
Opportunities to take on leadership roles within the team or the larger Reply organization.

📝 Enhancement Note: The technical challenges and growth opportunities at Machine Learning Reply Germany are focused on designing and implementing cloud solution architectures, collaborating with data science and data engineering teams, and participating in the complete project lifecycle. The team encourages a culture of innovation, collaboration, and continuous learning.

💡 Interview Preparation

Technical Questions:

Cloud Services: Questions related to AWS, Azure, or Google Cloud, such as architecture design, deployment, and management.
Programming Languages: Questions related to Python, shell scripting, or Perl, such as code samples, algorithms, and data structures.
Big Data Technologies: Questions related to Spark, Hadoop, or Kafka, such as data processing, data modeling, and data analysis.
Databases: Questions related to specific database technologies relevant to the role, such as SQL, NoSQL, or graph databases.
Networks & Cluster Technologies: Questions related to specific network and cluster technologies relevant to the role, such as network protocols, network security, or cluster management.
DevOps & MLOps: Questions related to DevOps and MLOps principles, such as infrastructure as code, continuous integration, and continuous deployment.

Company & Culture Questions:

Questions related to Machine Learning Reply Germany and the Reply group, such as company history, company culture, and company values.
Questions related to the role, team dynamics, and career growth opportunities, such as team structure, project management, and leadership development.

Portfolio Presentation Strategy:

Highlight examples of cloud solution architectures designed and implemented using AWS, Azure, or Google Cloud.
Showcase case studies demonstrating collaboration with data science and data engineering teams on data-intensive applications.
Provide detailed documentation and case studies demonstrating the complete project lifecycle, from conceptualization to implementation.

📝 Enhancement Note: The interview preparation at Machine Learning Reply Germany is designed to assess technical skills, cultural fit, and potential for growth within the organization. Candidates should be prepared to provide detailed documentation and case studies demonstrating their technical skills and ability to collaborate effectively with other teams.

📌 Application Steps

To apply for this cloud engineer position at Machine Learning Reply Germany:

Submit your application through the application link provided.
Prepare a portfolio showcasing examples of cloud solution architectures designed and implemented using AWS, Azure, or Google Cloud, as well as case studies demonstrating collaboration with data science and data engineering teams on data-intensive applications.
Research Machine Learning Reply Germany and the Reply group to demonstrate cultural fit and enthusiasm for the role.
Prepare for technical assessments or case studies that may involve designing and implementing cloud solution architectures, collaborating with other teams, and participating in the complete project lifecycle.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Cloud Engineer (m/f/d)