• Design, build, maintain, and operationalize data pipelines for high volume and complex data using appropriate tools and practices in development, test, and production environments. • Collaborate within an agile, multi-disciplinary team to deliver optimal data integration and transformation solutions • AAnalyze data requirements (functional and non-functional) to develop and design robust, scalable automated, fault-tolerant data pipeline solutions for business and technology initiatives • Profile data to assess the accuracy and completeness of data sources and provide feedback in data gathering sessions • Develop and design data mappings, programs, routines, and SQL to acquire data from legacy, web, cloud, and purchased package environments into the analytics environment • Understand and apply the appropriate use of ELT, ETL, data virtualization, and other methods to optimize the balance of minimal data movement against performance, and mentor others on their appropriate use • Drive automation of data pipeline preparation and integration tasks to minimize manual and error-prone processes and improve productivity using modern data preparation, integration, and AI-enabled metadata management tools and techniques • Leverage auditing facilities that will enable monitoring of data quality to detect emerging issues. • Deploy transformation rules to cleanse against defined rules and standards • Participate in architecture, governance, and design reviews, identifying opportunities and making recommendations • Participate in health check assessments of the existing environment and evaluations of emerging technologies • Collaborate with architects to design and model application data structures, storage, and integration in accordance with enterprise-wide architecture standards across legacy, web, cloud, and purchased package environments