Design, build, and maintain scalable data pipelines and ETL/ELT processes Develop and optimize data architectures, data lakes, and data warehouses Collect, process, and clean large datasets from various sources (structured and unstructured) Ensure data quality, integrity, and reliability across all data systems Collaborate with data scientists, analysts, and stakeholders to support data needs Implement data models and database schemas to support business requirements Monitor and troubleshoot data pipeline performance and failures Optimize data storage and retrieval for performance and cost-efficiency Integrate data from third-party APIs, cloud services, and internal systems Apply best practices in data governance, security, and compliance Automate workflows and data processing tasks using scripting and orchestration tools Maintain documentation for data pipelines, systems, and processes Work with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure) Support real-time and batch data processing systems