Data Engineer

5 days ago

Remote, Czech Republic Link Group Full time
  • Proven experience as a Data Engineer or in a similar data-focused role.
  • Strong Python programming skills with hands-on experience in data engineering.
  • Solid knowledge of AWS cloud services (S3, Glue, Redshift, Lambda, etc.).
  • Expertise in Apache Airflow or similar orchestration tools.
  • Experience working with Spark and Glue for data processing.
  • Familiarity with CI/CD, automation frameworks, and version control (Git).
  • Strong problem-solving skills and the ability to work in cross-functional teams.
  • Excellent communication skills in English.
Nice to Have:
  • Experience with Kubernetes, Docker, or other container orchestration tools.
  • Knowledge of data governance and security best practices.
  • Exposure to streaming platforms (e.g., Kafka).
About the Role:

We are seeking a skilled Data Engineer to join our team and help design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong Python coding skills, experience in AWS cloud services, and expertise in orchestration tools like Apache Airflow. You will be responsible for integrating automation solutions, optimizing data workflows, and ensuring smooth operations across data engineering processes.

Tech Stack:
  • Programming: Python
  • Cloud: AWS (e.g., S3, Glue, Lambda, EC2, Redshift)
  • Data Orchestration: Apache Airflow
  • Data Processing: Spark, Glue
  • Databases: Relational & NoSQL databases
  • Other: CI/CD pipelines, automation tools, Git
,[Design, develop, and maintain robust, scalable data pipelines and ETL workflows., Leverage Apache Airflow for orchestration and automation of complex data processes., Work with AWS services to manage and optimize cloud-based data solutions., Integrate automation tools to enhance platform efficiency and reliability., Collaborate closely with data scientists, analysts, and other engineers to deliver high-quality data solutions., Troubleshoot and optimize existing data workflows for performance and scalability., Support the implementation of Spark- and Glue-based solutions for big data processing.] Requirements: Python, Data engineering, AWS Cloud, AWS S3, Glue, Redshift, AWS Lambda, Apache Airflow, Spark, Git, Kubernetes, Docker, Security, Kafka Tools: Agile, Scrum.

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