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Wallet icon Coin icon Rate 120 000 CZK - 140 000 CZK / month info
Timer icon Form of cooperation Full-time / 50% 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 possibility of extension
Period of cooperation 09.03.2026 - 08.03.2027
Start date 09.03.2026 or by agreement
Technology
  • AWS Amazon Web Services
  • Python
  • TypeScript
Languages
  • English flag English - active, B2/C1/C2

Project description

  • Design and development of scalable ETL pipelines in Python for extracting, transforming, and loading data from multiple source systems
  • Implementation and optimization of data workflows in the AWS environment (Lambda, Glue, S3, Step Functions) with an emphasis on scalability, reliability, and cost-effectiveness
  • Development and maintenance of REST API in TypeScript (Node.js) for data access and integration scenarios
  • Creation and optimization of complex SQL queries and PLSQL functions/procedures for transformations, validations, and reporting
  • Setting up and performing unit and integration tests for ETL processes, APIs, and data transformations
  • Monitoring and troubleshooting data pipelines, performance tuning, and root-cause analysis of incidents
  • Collaboration with data analysts, architects, and business stakeholders in the design of data models and technical solutions
  • Ensuring data quality, documenting ETL processes, APIs, and data flows
  • Adherence to security standards, working with version control systems and CI/CD in a cloud environment

Project requirements

  • Advanced experience with:
    • Python for ETL development and data processing (min. 3 years of experience)
    • AWS services relevant to data engineering (Lambda, Glue, S3, workflow orchestration)
  • Experience with:
    • developing REST API in TypeScript / Node.js
    • designing and optimizing SQL and PLSQL (functions, procedures, performance tuning)
    • working with large data volumes and data analytics
  • Advanced knowledge of:
    • data models, transformations, and data validation
    • testing code and data pipelines (unit, integration tests)
  • Knowledge of:
    • Git and CI/CD principles
    • basic principles of security and DevOps in a cloud environment
  • Advantageous:
    • experience in designing scalable cloud architectures
    • practice in an international team and communication with business stakeholders
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