Machine Learning Reply
Cloud and Data Engineer (m/f/d)
Job Description
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:
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Consult with clients to understand their business objectives, data engineering, and machine learning requirements.
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Design and develop cloud-based data and machine learning solutions using AWS, GCP, and/or Azure services and tools.
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Build and maintain scalable data pipelines, ensuring data quality and reliability.
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Collaborate with cross-functional teams to implement machine learning models and data pipelines.
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Stay up to date with the latest trends and advancements in cloud-based technologies, data engineering, and AI.
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Advise clients on strategic decisions and take ownership of the implementation of the suggested solutions.
What we offer you:
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Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.).
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Broaden your skills through interdisciplinary work and training in the areas of data engineering, cloud architecture, and data science.
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Benefit from industry-leading cooperations in the cloud, BI, and AutoML fields.
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A very active social program, including training, conferences, team buildings, Reply Exchange, communities of practice, and hackathons.
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Work in an open, flat environment within a broad Reply knowledge-sharing network.
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Award-winning office space in downtown Munich with access to “Stammstrecke.”
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State-of-the-art equipment of your choice.
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Public transport ticket with Deutschlandticket.
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Gym membership subsidy for a gym of your choice.
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Flexible work environment between client, Reply office, and remote work.
Requirements
Minimum Qualifications:
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Previous experience and/or interest in the area of Artificial Intelligence projects and Cloud.
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Project experience, either through internships or similar corporate experience, in designing complex cloud-based solutions.
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Experience in Python, Java, and SQL.
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Knowledge of Distributed Data Processing technologies like Hadoop or Spark.
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Successfully completed university studies with a strong quantitative background, for example in Business Informatics, Data Science, Informatics, Computer Science, or similar.
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Ability to convincingly communicate and present analytical results to management.
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Interest and/or experience in the full lifecycle of Data: from Cloud Infrastructure, Data Engineering, Data Analytics, and Visualization to ML Engineering and MLOps.
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Fluent in English and able to speak German at least at a B2 Level.
Desired Qualifications:
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Extensive experience working with cloud technologies (AWS, Azure, GCP).
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Certificates from Cloud Providers are an advantage.
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Understanding of underlying database infrastructure (data models, ETL processes).
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Kubernetes and/or Docker knowledge is a plus.
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Experience in Infrastructure as Code technologies (Terraform, CodeFormation) is a plus
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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 (j.heepen@reply.de).