Data Engineer (m/f/d)

Katowice, Poland

At Machine Learning Reply Poland we strive to work on leading-edge data science projects with our clients for which we are seeking engineering consultants to work on Machine Learning products.

Machine Learning Reply, with its sister company in Italy and over 8500 employees at Reply globally, is a fast-growing consultancy focused on solving problems with Data Science and the right organizational frameworks as their backbone. We are a tight knit, laid back, but seriously motivated unit that aims to be involved at conferences and in community of practice with our tech partners.

We offer tailor-made end-to-end solutions in the Data Science area that cover the entire project life cycle - from initial strategy consulting to data architecture and infrastructure issues to data processing and modeling using machine learning algorithms.

We have extensive expertise in the broad Data Science spectrum in all key industries of the German HDAX-companies. With focus on open source and cloud technologies we enable our customers to successfully introduce and implement new data-driven solutions and to optimize already existing processes and products.


  • You will support the successful implementation of customer products related to Big Data, Data Engineering, and/or Data Warehouses.
  • Build and maintain scalable Data Platforms and ML Platforms on Cloud (AWS, Azure, Google Cloud) or on-premise, considering DevOps paradigms.
  • You enjoy brainstorming, conceptualization and final implementation. You therefore love to accompany the complete LifeCycle by creating specifications, code and presentations for your solutions.
  • As part of the Reply network, you join communities of practice, participate in hackathons and use all available learning resources


  • We are happy to see that you have a university degree in (business) computer science, mathematics, statistics or similar.
  • You have experience with cloud services from AWS or Azure, alternatively you have substantial knowledge with on-premise solutions, and/or Kubernetes. 
  • You have interest in ETL, and workflow orchestration tools such as Airflow, Luigi..
  • Good Knowledge of databases, and have had some experience with Big Data technologies such as Spark, Hadoop or Kafka.
  • You are familiar with a programming language such as Python, Scala, shell scripting or even Perl. 
  • Fluency in English and German would be beneficial.


  • Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.)
  • Very active group social program - including conference funding, team building, group events, Reply Exchange
  • Recognition for Innovation to foster your personal development
  • Work in an open, flat environment, within a broad Reply knowledge sharing network (more than 90 autonomous Reply groups across 8 countries)
  • Training and certification encouraged
  • Home-office contracts
  • State of the art work equipment
Updated: 4 days ago
Job ID: 3722729
About Machine Learning Reply
As part of the Reply network with over 8.000 employees and a global footprint, Machine Learning Reply has extensive expertise in the Data Science field across all key industries of our DAX100 clients. The consulting firm offers customized end-to-end data science solutions, covering the entire project lifecycle: whether it is the initial strategy consulting to identify high value cases, project management in classic and agile roles or from data architecture and infrastructure topics to the collection, processing, and quality assurance of data, using state-of-the art Machine Learning algorithms. We empower clients to successfully launch new data driven business initiatives, as well as optimizing already existing processes and products. The company focuses thereby on distributed open source and cloud technologies, to assist companies on their data journey in the most suitable way.
51-200 employees
Management Consulting
Luise-Ullrich-Straße, München, Deutschland
Luise-Ullrich-Straße, München, Deutschland
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Contact Person
Isabel Banzerus
Recruiting Team
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