Design, build, and manage scalable and robust data pipelines using big data technologies.
Develop and optimize ETL processes to support large-scale data ingestion, transformation, and delivery.
Implement data lakes, warehouses, and real-time data processing frameworks.
Collaborate with data scientists and analysts to support machine learning model deployment and analytical use cases.
Monitor data workflows and troubleshoot performance issues.
Ensure data quality, governance, and security best practices.
Work with tools and platforms such as Hadoop, Spark, Kafka, Hive, and cloud-based services (e.g., AWS, Azure, GCP).
