{"id":4447,"date":"2024-11-19T17:00:19","date_gmt":"2024-11-19T17:00:19","guid":{"rendered":"https:\/\/www.whitehattoolbox.com\/jobs\/consultant-business-consulting-pharma-data-engineering\/"},"modified":"2024-11-19T17:00:19","modified_gmt":"2024-11-19T17:00:19","slug":"consultant-business-consulting-pharma-data-engineering","status":"publish","type":"post","link":"https:\/\/www.whitehattoolbox.com\/jobs\/consultant-business-consulting-pharma-data-engineering\/","title":{"rendered":"Consultant – Business Consulting (Pharma Data Engineering)"},"content":{"rendered":"

Responsibilities :<\/b><\/span>1. Data Pipeline Development: Design, build, and maintain robust data pipelines to collect, process, and transport data from various sources to the data warehouse or data lake.
\n 2. Data Modeling: Develop and optimize data models, schemas, and structures to support efficient data storage and retrieval, ensuring data is organized for analytics and reporting.
\n 3. ETL Process Management: Manage complex ETL (Extract, Transform, Load) processes, including data transformation, validation, and cleansing, while ensuring data quality and integrity.
\n 4. Performance Optimization: Optimize data pipelines and database systems for improved performance, scalability, and responsiveness to meet growing data demands.
\n 6. Data Integration: Implement data integration solutions for real-time and batch data streaming, ensuring that data is accessible and available to users and applications.
\n 7. Data Security and Compliance: Implement and maintain data security measures and ensure compliance with relevant data protection and privacy regulations, such as GDPR or HIPAA.
\n 8. Automation: Automate repetitive data engineering tasks and processes to reduce manual effort and improve efficiency.
\n 9. Monitoring and Troubleshooting: Set up monitoring systems to track data pipeline health and troubleshoot issues to minimize downtime or data loss.
\n 10. Collaboration: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements, business processes and provide support for their analytics and reporting needs.
\n 11. Data Warehouses and Data Lakes: Familiarity with data warehousing and data lakes used to store and manage large volumes of pharmaceutical data efficiently.
\n 12. Understanding of Pharma related datasets: IQVIA, PLD, OneKey, Sales Data, Activity Data, Clinical trial data, Manufacturing data, transitional data etc.<\/span>Additional Responsibilities :<\/b><\/span>Advance SQL, window functions, joins and query optimization techniques.
\n Advanced analytics and machine learning is a plus.
\n Nice to have CI CD pipelines, Git or DevOps, hands-on Unity Catalogue\/PurView capability <\/p>\n