Informacje o stanowisku
Hadoop Data Engineer (GCP, Spark, Scala) – Kraków / Hybrid
We are looking for an experienced Hadoop Data Engineer to join a global data platform project built in the Google Cloud Platform (GCP) environment. This is a great opportunity to work with distributed systems, cloud-native data solutions, and a modern tech stack. The position is based in Kraków (hybrid model – 2 days per week in the office).
Work model:
- Hybrid – 2 days per week from the Kraków office (rest remotely)
- Opportunity to join an international team and contribute to global-scale projects
Must-have qualifications:
- Minimum 5 years of experience as a Data Engineer / Big Data Engineer
- Hands-on expertise in Hadoop, Hive, HDFS, Apache Spark, Scala, SQL
- Solid experience with GCP and services like BigQuery, Dataflow, DataProc, Pub/Sub, Composer (Airflow)
- Experience with CI/CD processes and DevOps tools: Jenkins, GitHub, Ansible
- Strong data architecture and data engineering skills in large-scale environments
- Experience working in enterprise environments and with external stakeholders
- Familiarity with Agile methodologies such as Scrum or Kanban
- Ability to debug and analyze application-level logic and performance
Nice to have:
- Google Cloud certification (e.g., Professional Data Engineer)
- Experience with Tableau, Cloud DataPrep, or Ansible
- Knowledge of cloud design patterns and modern data architectures
Hadoop Data Engineer (GCP, Spark, Scala) – Kraków / Hybrid
We are looking for an experienced Hadoop Data Engineer to join a global data platform project built in the Google Cloud Platform (GCP) environment. This is a great opportunity to work with distributed systems, cloud-native data solutions, and a modern tech stack. The position is based in Kraków (hybrid model – 2 days per week in the office).
Work model:
- Hybrid – 2 days per week from the Kraków office (rest remotely)
- Opportunity to join an international team and contribute to global-scale projects
,[Design and build large-scale, distributed data processing pipelines using Hadoop, Spark, and GCP, Develop and maintain ETL/ELT workflows using Apache Hive, Apache Airflow (Cloud Composer), Dataflow, DataProc, Work with structured and semi-structured data using BigQuery, PostgreSQL, Cloud Storage, Manage and optimize HDFS-based environments and integrate with GCP components, Participate in cloud data migrations and real-time data processing projects, Automate deployment, testing, and monitoring pipelines (CI/CD using Jenkins, GitHub, Ansible), Collaborate with architects, analysts, and product teams in Agile/Scrum setup, Troubleshoot and debug complex data logic at the code and architecture level, Contribute to cloud architecture patterns and data modeling decisions Requirements: Big Data, Hadoop, Hive, HDFS, Apache Spark, Scala, SQL, GCP, BigQuery, PUB, Airflow, DevOps, Jenkins, GitHub, Ansible, Tableau, Google Cloud
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