The Data Analytics Engineer has advanced technical skills, is able to manage complex and iterative projects, and has the business experience to understand and communicate with non-technical users. Projects involve relationships with a variety of teams. Specifically, the position will work with the FPO Business Operations and Analytics team, the EIM (Enterprise Information Management)- and Enterprise Analytics teams, FPO Finance and Decision Support Systems teams, data governance staff, business analysts, end-users, data owners, and BI and data management professionals to:

• Provide expertise and drive initiatives for data sourcing, data profiling, and data management standardization and process development
• Standardize data infrastructure processes and approaches including ETL technologies and mapping standards, data modeling standards, data quality approaches, and validation processes, data management for reference and master data, metadata management approaches, and standards
• Design and build data pipelines, data streams, and system integrations
• Support ad-hoc data requests from internal/external clients
• Develop, maintain, and support data applications and reports
• Data profiling and data characterization using statistics and data analysis to understand data and inform the development of data infrastructure to support clinical and operational requirements
• Data model development using data science and analytic methods along with stakeholder requirements to inform data infrastructure projects on database designs that facilitate data usage, reduce data redundancy and promote UCSF data governance standards
• Data sourcing using data flow diagraming and data profiling to develop approaches and specifications for sourcing data into target data marts/databases: includes ETL mapping, data modeling, data validation
• Technical project management including project intake and estimating processes, data team resource planning and management, data infrastructure planning and goals
• Define systems and applications to support various functions. May provide customer service, troubleshooting, and maintenance
• Planning, design, develop, implement, and administer data-based systems and reporting capacities that acquire, prepare, store and provide access to data and metadata to end-users for monitoring
• Maintain and optimize new and existing systems, and migrate data and systems as needed. Ensure integrity and completeness of data and workflow, the analytics data engineer manages and/or develops data practices, methods, databases, and information systems, as well as guidelines, dictionaries, registries, and/or services
• Design systems, data products, and/or data production processes while focusing on data curation, data exchange, data security, data integrity, quality assurance, and information environments. Engage team on understanding data limitations, definitions, and creating meaningful data capture design, reporting, interpreting, data integrity, and database management.
• Regularly monitor data load processes to identify and resolve issues
• Collaborate with analytics and business teams across the organization to implement:
  • (1) processes and systems to improve data models, increase data accessibility, and foster data-driven decision-making and
  • (2) processes and systems to monitor data quality and ensure the production data is as accurate and complete as possible for key stakeholders
• Assist with the development of a comprehensive framework and provide recommendations for the data architecture, data storage, data integration, data quality, and data models
• Assist with technology improvements to ensure continuous enhancement of the data platform