Design and implement scalable data pipeline using modern data platform (Spark, Flink, Kafka, Airflow) Build and manage ETL/ELT processes to ingest data from various sources (databases, APIs, files, message queues) Develop and maintain data models and data warehouse / datalake architectures Ensure high data quslity and implement data validation, observability and monitoring frameworks Collaborate with other team such as data analyst, data scientist and business stakeholders to understand data requirements and deliver data solutions Optimize performance of big data processing jobs and ensure cost efficiencient data infrastructure Advocate for best practices in data engineering, including documentation, testing, version control and other with team