Data Engineer – Data Lake (f/m/x)

You will join an international project within the healthcare and life sciences industry, focused on building and evolving a modern Data Lake platform supporting large-scale data processing and analytics. The solution enables data-driven decision-making in a highly regulated environment, with a strong emphasis on data quality, security, and compliance. The environment is cloud-based and leverages modern big data technologies and best engineering practices.As a Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines and Data Lake architecture. You will work closely with cross-functional teams, including data scientists and business stakeholders, to deliver reliable and efficient data solutions.Your tasksDesigning and developing scalable data pipelines for batch and real-time data processingBuilding and optimizing Data Lake architecture for analytical use casesIntegrating multiple data sources and ensuring seamless data flow across systemsEnsuring data quality, consistency, and governance (data lineage, access control)Optimizing storage and processing performance using modern data formats and partitioning strategiesMonitoring, troubleshooting, and improving data pipeline performanceCollaborating with stakeholders to translate business needs into technical solutionsFollowing best practices in data engineering and continuously improving the platformRequirementsStrong experience in Data Engineering or Big Data-related rolesProficiency in Python, Scala, or JavaHands-on experience with tools such as Apache Spark, PySpark, or similar frameworksPrevious work with Data Lake technologies (e.g., AWS S3, Azure Data Lake, Databricks, BigQuery)Knowledge of ETL/ELT processes and orchestration tools (e.g., Airflow, Data Factory)Good understanding of SQL and data modelingExperience with distributed systems and large-scale data processingFamiliarity with Docker and KubernetesStrong analytical and problem-solving skillsFluent in Polish requiredResiding in Poland requiredNice-to-have requirementsExperience with streaming technologies (e.g., Kafka)Knowledge of data governance toolsFamiliarity with CI/CD processes in data projects