05 Senior Data Engineer

Data Modeling and Metrics Development: Develop and maintain sophisticated data models to support transactional, analytical, and predictive use cases. Define and compute key metrics such as customer acquisition, operational efficiency, and overall business performance. Enable stakeholders to create tailored metrics and reports for data-driven decision-making Analytics Solutions and Data Products: Design advanced analytics solutions leveraging the data platform to provide actionable business insights. Build scalable and reusable data products to support cross-functional teams, including marketing, operations, and finance. Data Mart Management: Manage and maintain the SAS Data Mart, ensuring the integrity and security of ETL processes and underlying datasets. Ensure high availability and performance of data marts by optimizing storage and retrieval mechanisms. Data Quality and Governance: Implement robust quality assurance processes to monitor and validate data accuracy, completeness, and timeliness. Develop and enforce data governance policies to maintain high data standards. Build metadata management systems and a centralized data catalog to enhance data accessibility. Automation and Process Optimization: Automate data pipeline processes to enhance operational efficiency and scalability. Optimize the performance of data transformation and query processes to reduce latency and improve system responsiveness. Collaboration and Continuous Improvement: Collaborate with data scientists, business analysts, and other engineers to align technical solutions with business goals. Stay updated with industry trends and incorporate innovative tools and methodologies into the data ecosystem.