Data Engineer Automation & Innovation Department, WARSZAWA

• Minimum 3 years of experience in a Data Engineering role.
• Practical experience with Cloud (preferably GCP) services, including BigQuery, Dataflow, Google Cloud Storage (GCS), Data Catalog, and dbt.
• Advanced SQL proficiency, including writing complex queries, query optimization, Common Table Expressions (CTEs), window functions, and related advanced SQL techniques.
• Python coding skills (experience with Pandas and NumPy is a plus)
• Experience working with Apache Airflow for pipeline orchestration, workflow automation, monitoring, data quality validation, alerting, and troubleshooting.
• Experience with Apache Spark, Hadoop, and Hive for large-scale data processing.
• Experience designing, developing, testing, maintaining, and optimizing ETL/ELT pipelines for batch and streaming data processing, including Apache Kafka, API-based data ingestion.
• Experience designing and implementing data integration solutions, data warehouse architectures, data models, and data layers to support analytics and reporting.
• Experience implementing and maintaining CI/CD pipelines and using GitLab for version control and technical documentation.
• Experience working in Agile/Scrum
• Good command of English.

Nice to have:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
• Basic understanding of Machine Learning and MLOps principles
• Strong understanding of data governance principles, including metadata management and data quality frameworks.
• Experience in international or multi-country data projects is preferred.
• Strong communication skills to translate technical findings into business-oriented insights.
• Self-starter with a continuous learning mindset and strong attention to detail.

,[Build and maintain data ingestion processes from various sources into the Data Lake., Design, develop, and optimize complex data pipelines for reliable data flow., Build, develop, and maintain frameworks that facilitate the construction of data pipelines., Implement end-to-end testing frameworks for data pipelines., Collaborate with data analysts and scientists to ensure the delivery of quality data., Ensure robust data governance, security, and compliance practices., Explore and implement emerging technologies to improve data pipeline performance., Utilize and integrate data from various source system types, including Kafka, MQ, SFTP, databases, APIs, and file shares] Requirements: BigQuery, Google Cloud Storage, SQL, Apache Spark, Hadoop, Hive, Testing, ETL, Apache Kafka, Data warehouse, Data models, Data engineering, Cloud, GCP, pandas, NumPy, Apache Airflow, CD, GitLab, Degree, Data science, Machine Learning, Communication skills