Pipeline Development Design write and maintain modular Python scripts and frameworks to automate endtoend ETLELT workflows Data Transformation Clean deduplicate reformat and encrypt complex datasets using data manipulation libraries Data Warehouse Architecture Build optimal data models and schemas within cloud data platforms to support reporting requirements Orchestration Automation Schedule and monitor pipeline executions using workflow orchestration tools Performance Optimization Tune complex SQL queries and Python code to eliminate processing bottlenecks and handle growing data volumes Quality Assurance Monitoring Implement proactive logging handling and data quality validation checks to guarantee pipeline reliability Collaboration Partner with business teams to translate ambiguous data needs into concrete technical implementations