Data Engineer (Databricks) @ Xebia sp. z o.o.

Your profile: 2–4 years of professional experience in Data Engineering, Software Engineering, or Operational Engineering, experience with Databricks and PySpark for large-scale data processing, strong proficiency in Python, including building and debugging data pipelines and automation scripts, hands-on experience with Apache Airflow (DAG development, operators, troubleshooting), very good knowledge of SQL, including complex joins, window functions, and JSON-based data, experience working with big data technologies such as Hadoop, Spark, and Hive, ability to design, develop, test, and deploy scalable data processing pipelines, strong understanding of data modeling, data warehousing, and ETL processes, excellent problem-solving skills, ability to work in a team environment, willingness to learn new tools and technologies, experience with Agile development methodologies, knowledge of DevOps practices, experience working with cloud-based platforms such as AWS or Azure, experience with containerization using Docker, experience with version control systems like Git, strong analytical and logical thinking, excellent communication skills, ability to work in a fast-paced environment, willingness to take on new challenges, and passion for data engineering.