Senior Data Engineer Hadoop Spark

• 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

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

,[Define and contribute to software design and development using Pyspark, Automate testing of new and existing components, Promote development standards through code reviews and mentoring, Provide production support and troubleshooting, Implement tools and processes ensuring performance, scalability and monitoring, Collaborate with Business Analysts to interpret and implement requirements, Participate in planning, sprint reviews and retrospectives, Contribute to system architecture and design] Requirements: PySpark, Scala, Airflow, Hadoop, Spark, Hive, Yarn, ETL, SQL, REST, Unix, Linux, Data pipelines, Git, GitHub, Jenkins, Ansible, Jira, Big data, Elasticsearch, Java APIs, DevOps, Spark Streaming, Apache Airflow, Python, PL/SQL Additionally: Home office, Knowledge sharing, Life insurance, Sport subscription, Training budget, Private healthcare, International projects, Integration events, Free coffee, Playroom, Free snacks, Free beverages, In-house trainings, In-house hack days, Modern office, Free fruits.