Data Engineer (Medical Quality Management)

Company Background

Our client is one of the leading providers for quality management solutions (QMS). Their primary customers are pharma and medical companies. They support more than 700 on-premise and cloud implementations in more than 30 countries across the world. The client offers analytical solutions that help their customer to lower risk, increase efficiency allowing manufacturers, suppliers, and distributors to collaborate in a seamless and integrated environment.

Project Description

Our goals are:


  • To integrate data from multiple data sources by building AWS hosted data lake, which should enable data exploration for Data Science team;
  • To get insights from the Data and build dedicated ML-based algorithms and models to automate defect identification and classification;
  • To streamline and speed up root cause analysis;
What you’ll do
  • Architect/design and implement POC for Data Lake on AWS;
  • Closely work with Data Science team and business to gather requirements for further development;
  • Design and implement analytical pipeline to clean, transform and prepare data for machine learning algorithms;
  • Closely work with Data Science team to design and implement pipeline to train/validate machine learning models;
  • Support Data Science team;
Apache Spark
Scala / Python / Java
AWS Glue
Job Requirements



  • Experience with cloud based analytical solutions (AWS preferred);
  • Practical experience with implementing complicated data processing and analytics pipelines;
  • Proficient in Apache Spark;
  • Experience with AWS Glue is a plus;
  • Fluent in SQL and one of the programming languages: Scala, Python, Java;
  • Strong analytical and problem-solving skills;




  • Excellent communication and presentation skills;
  • Background in data mining and statistical analysis;
  • Ability to work with cross-functional teams in a highly collaborative manner;


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