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Wallet icon Coin icon Rate 150 000 CZK - 180 000 CZK / month info
Timer icon Form of cooperation Full-time / 60% Remote
Briefcase icon Sector Healthcare and Pharmacy
Location icon Location Praha

info The reward is calculated upon delivery of 20 MD per month (1MD=8h)

Project duration 12 months with the possibility of extension
Period of cooperation 15.12.2025 - 14.12.2026
Start date 15.12.2025 - 01.01.2026
Technology
  • AWS Amazon Web Services
  • SQL
  • Python
  • Databricks
  • Apache Airflow
Languages
  • English flag English - active, B2/C1/C2
  • Slovak or Czech flag Slovak or Czech - native

Project description

  • collaboration on a long-term project for a global pharmaceutical company that accelerates the development of new drugs using scientific data and AI
  • development and optimization of data pipelines and models in the field of pharma research and scientific data, working with complex datasets
  • development, orchestration, and monitoring of ETL/ELT processes using Apache Airflow and DBT
  • design and implementation of data models and schemas for analytical and operational needs
  • working with tools and technologies such as Python, Databricks, SQL, GitHub Actions and AWS
  • close collaboration with data analysts, researchers, and other members of the data team
  • collaboration takes place in a combined mode of onsite 2 days a week (Prague) and remote, after training, the mode is flexible

Project requirements

  • Advanced experience with:
    • Python for creating data transformation scripts and integration components
    • Databricks and its environment for processing big data
    • AWS services for data engineering (e.g. S3, Lambda, Glue)
    • Apache Airflow for orchestrating data flows
    • SQL (including query optimization and creating complex joins)
  • Experience with:
    • GitHub and CI/CD workflows using GitHub Actions
    • designing and creating ETL/ELT pipelines
    • data modeling and designing data schemas for analytical and operational purposes
  • Knowledge of:
    • DBT as a tool for data transformation within the ELT architecture
  • Advantage:
    • experience with data in the field of pharma or scientific research
    • orientation in working with unstructured and semi-structured data
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