Data Engineer with Python

Who we are

High-Tech Systems & Software develops an enterprise line of business applications that covers a broad range of platforms, technologies, and services.

We are a team of five people working on a unique hi-tech project, including advanced analytics and machine learning. We are looking for an experienced data engineer in Python to join our team. We are looking for a proactive person interested in learning new things and coming up with new solutions and ideas. Your role will help us develop the software platform for six countries by supporting the team with Python-based data processes. We work in an agile environment, so each day is a challenge, and you will probably never get bored. You will use various Python environments to implement complex data flows.
To succeed in this data engineering with Python position, you should have strong analytical skills and the ability to combine data from different sources. Good knowledge of applying Python in data engineering is required.

What are you going to do:

  • Analyze and organize raw data
  • Build data systems and pipelines
  • Interpret trends and patterns
  • Conduct complex data analysis and report on results
  • Prepare data for prescriptive and predictive modeling
  • Combine raw information from different sources
  • Explore ways to enhance data quality and reliability
  • Collaborate with data scientists and architects on several projects

What we are looking for:

  • Good experience using Python for data engineering
  • Analytical mindset, capable of identifying faint variances in data
  • Medium level understanding of statistical concepts
  • Experience in working on fairly large volumes of relational data
  • Experience in working on fairly large volumes of semi-structured data (files – CSV, Parquet)

Nice-to-have skills:

  • Data analysis using Spark
  • Experience with Azure Data Factory and/or Synapse Pipelines

What you could expect:

  • Competitive salary and growth perspectives
  • Motivated international teams
  • Flexible working hours
  • Additional annual vacation days (starting at 21 and going up to 24)
  • Private health coverage
  • Meal tickets
  • Budget for annual professional training sessions