About this role

Senior Data Consultant (Hadoop, Spark) GFT Poland Daily tasks: - 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 Musts: PySpark, Scala, Airflow, Hadoop, Spark, Hive, Yarn, ETL, SQL, REST, Unix, Linux, Data pipelines, Git, GitHub, Jenkins, Ansible, Jira, Big data 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 Openness to work 2 days a week from our client's office (Kraków) 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.

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