Cloud and Data Engineer (m/f/d)

Company overview:

Machine Learning Reply provides customized end-to-end solutions in the data science field that cover the entire project life cycle – from initial strategic consulting to data architecture and infrastructure topics, through to data processing and quality assurance using machine learning algorithms. We enable our customers to successfully implement new data-driven business models as well as optimize existing processes and products – with a focus on open-source and cloud technologies.

About the role:

We are seeking a talented and highly skilled Cloud and Data Engineer Consultant with a technical background to join our team. As a Consultant, you will be responsible for providing expert guidance and technical support to our clients in leveraging cloud-based data and machine learning solutions, with a specific focus on AWS, GCP, or Azure. The ideal candidate for this role possesses a solid background in Software Development, knowledge of Cloud Solutions, and shares our passion for Data and AI.

Responsibilities:

• Consult with clients to understand their business objectives, data engineering, and machine learning requirements.
• Design and develop cloud-based data and machine learning solutions using AWS, GCP, and/or Azure services and tools.
• Build and maintain scalable data pipelines, ensuring data quality and reliability.
• Collaborate with cross-functional teams to implement machine learning models and data pipelines.
• Stay up to date with the latest trends and advancements in cloud-based technologies, data engineering, and AI.
• Advise clients on strategic decisions and take ownership of the implementation of the suggested solutions.

What we offer you:

• Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.).
• Broaden your skills through interdisciplinary work and training in the areas of data engineering, cloud architecture, and data science.
• Benefit from industry-leading cooperations in the cloud, BI, and AutoML fields.
• A very active social program, including training, conferences, team buildings, Reply Exchange, communities of practice, and hackathons.
• Work in an open, flat environment within a broad Reply knowledge-sharing network.
• Award-winning office space in downtown Munich with access to “Stammstrecke.”
• State-of-the-art equipment of your choice.
• Public transport ticket with Deutschlandticket.
• Gym membership subsidy for a gym of your choice.
• Flexible work environment between client, Reply office, and remote work.

Minimum Qualifications:

• Previous experience and/or interest in the area of Artificial Intelligence projects and Cloud.
• Project experience, either through internships or similar corporate experience, in designing complex cloud-based solutions.
• Experience in Python, Java, and SQL.
• Knowledge of Distributed Data Processing technologies like Hadoop or Spark.
• Successfully completed university studies with a strong quantitative background, for example in Business Informatics, Data Science, Informatics, Computer Science, or similar.
• Ability to convincingly communicate and present analytical results to management.
• Interest and/or experience in the full lifecycle of Data: from Cloud Infrastructure, Data Engineering, Data Analytics, and Visualization to ML Engineering and MLOps.
• Fluent in English and able to speak German at least at a B2 Level.

Desired Qualifications:

• Extensive experience working with cloud technologies (AWS, Azure, GCP).
• Certificates from Cloud Providers are an advantage.
• Understanding of underlying database infrastructure (data models, ETL processes).
• Kubernetes and/or Docker knowledge is a plus.
• Experience in Infrastructure as Code technologies (Terraform, CodeFormation) is a plus.
• Interest in (agile) project management.

What are you waiting for?

Join our team at Machine Learning Reply as a Cloud and Data Engineer Consultant in Munich!

If you have any further questions or would like to apply, please do not hesitate to write directly to Jonas Heepen ( ).

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