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Senior Data Engineer (Hadoop, Spark)

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Description

What will you do?


You will work as a key member of a technical team alongside Engineers, Data Analysts and Business Analysts, contributing to a collaborative Agile development process while designing, developing and maintaining scalable data solutions in a dynamic DevOps environment.

We offer

  • Hybrid work in Krakow (2 office days per week)
  • Working in a highly experienced and dedicated team
  • Benefit package tailored to your needs (medical, sport, lunch subsidy, life insurance, etc.)
  • Online training and certifications
  • Access to e‑learning platform
  • Social events
  • Experience with Pyspark or Scala development and design
  • Experience using scheduling tools such as Airflow
  • Knowledge of Hadoop ecosystem including Spark, Hive, YARN and ETL frameworks
  • Strong SQL and RESTful services knowledge
  • Experience working on Unix or Linux platforms
  • Hands-on experience building data pipelines using Hadoop components
  • Experience with Git, GitHub, Jenkins, Ansible and JIRA
  • Understanding of big data modelling using relational and non-relational techniques
  • Experience debugging code and communicating findings to development teams
Nice to have
  • Experience with Elasticsearch
  • Experience developing Java APIs
  • Experience in data ingestion processes
  • Understanding of cloud design patterns
  • Exposure to DevOps and Agile methodologies such as Scrum and Kanban
  • Experience with Spark streaming
  • Experience with Apache Airflow in production
  • Experience with Hadoop ecosystem in enterprise environments
  • Knowledge of Python backend services
  • Experience with Scala for high performance systems
  • Experience in data integration and ETL processes
  • Knowledge of PL/SQL
  • Experience with Linux and Unix system operations

Skills

What Senior Data Engineering jobs ask for — and how much of it you have →
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See also

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