Middle Data Engineer (Healthcare domain)

Bulgaria Czech Republic Europe Hungary Poland Portugal Remote (Ukraine) Ukraine Data Engineer Data Science Engineering

Required skills

Python / strong
Azure / good
Snowflake / good
Databricks / strong
English / strong

Sigma Software is looking for a motivated Data Engineer to join our growing engineering team. If you want to work in a close-knit team of Data engineers solving complex problems using advanced data collection, transformation, analysis, and monitoring, this opportunity is for you.

We look forward to having you on our team!


Our client is a leading medical technology company. The portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation is and always will be at the core of the company. The client is committed to creating better patient outcomes and experiences, no matter where they live or what they face. The client is innovating sustainably to provide healthcare for everyone, everywhere.


Project’s mission is to enable healthcare providers to increase their value by equipping them with our innovative technologies and services in diagnostic and therapeutic imaging, laboratory diagnostics, molecular medicine, and digital health and enterprise services.


  • Experience in data engineering and with cloud computing services solutions in the area of data and analytics, preferably with Azure
  • Conceptual knowledge of data analysis fundamentals, e.g., dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data
  • Knowledge of SQL and experience with the Python programming language
  • Excellent communication skills and fluency in business English
  • Understanding Big Data Data Bases such as Snowflake, BigQuery, etc. Snowflake is the preferred one
  • Experience in database development and data modeling, ideally with Databricks/Spark


  • Design, develop, optimize, and maintain squad-specific data architecture and pipelines that adhere to defined ETL and Data Lake principles
  • Discover, understand, and organize disparate data sources and structure them into clean data models with clear and understandable schemas
  • Contribute to the evaluation of new tools for analytical data engineering or data science
  • Suggest and contribute to training and improvement plans for analytical data engineering skills, standards, and processes


  • Diversity of Domains & Businesses
  • Variety of technology
  • Health & Legal support
  • Active professional community
  • Continuous education and growing
  • Flexible schedule
  • Remote work
  • Outstanding offices (if you choose it)
  • Sports and community activities


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