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Proficient in Epic event logging data model (metadata) and certified in EPIC EMR Clarity data warehouse reporting, Cogito Reporting workbench, and Cogito Radar applications, with advanced expertise in EPIC data and EPIC Clarity Data Model.
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In-depth knowledge of all relevant clinical informatics software and systems, and of the highly-complex concepts, principles, policies, methodologies, techniques, best practices, regulations, and standards practices involved with patient care and electronic medical data management in the UC health care system.
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Knowledge of controlled terminology, clinical workflows, user interface optimization, clinical decision support, rules development, data integration and mining, clinical ontologies and adoption of technology.
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Proficiency in understanding modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks.
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Experience with conceptualization, design and assistance in the implementation of new and existing systems, middleware, MDM, metadata, data quality, data warehouse and production architectures.
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Experience with any of the following: Data Architecture, Elastic Search, DBT, AirHow, Palantir Foundry, Data Quality tools, Collibra, MOM, Informatica, Spark, Snowflake, Teradata, SAP Business Warehouse, Business Objects Suite.
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Thorough knowledge of data governance framework including data warehouse, metadata management, data quality, reference data/master data, data quality and data modeling.
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The Data Warehouse Architect is responsible for data warehouse architecture and design and development of data and metadata model as well as ETL requiring multiple technologies.
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Experience in healthcare business intelligence (experience with CRO/Academic CRO preferred), data transformation/data modeling, metadata management, data security, data warehouse/data mart.
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Champion efforts to improve business performance through enterprise information solutions and capabilities, such as master data management, metadata management, business intelligence, content management, data integration, and related information management or information infrastructure components.
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Activities may include data quality engineering, metadata consolidation and integration, metamodel development and maintenance, repository management, data warehouse design and data mining, data security administration, and formulation of enterprise-specific data metrics.
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Sustained full-lifecycle technical leadership on data-intensive development projects (e.g. data warehouse, data lake, data transport systems, metadata management systems, data quality, analytics & reporting.
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Perform unit testing and regression testing of data integration solutions developed in Microsoft SSIS & ODI. Collaborate with the Business Intelligence (BI) Engineer to evolve the BI metadata design and assist in maintaining the enterprise metadata model.
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Design, develop, adapt, and maintain data warehouse architecture and relational databases that support data mining. Senior Consultant- Data Engineering. Customize storage and extraction, metadata, and information repositories.
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Experience with BI governance including data usage, metadata, data management, data quality, privacy, and security - 4 years. skills: Data Warehouse. Perform Tableau site administration in DEV, UAT, and PROD including organization, optimization, tuning, and ensuring the security of data using Tableau Server with a strong understanding of security policies and best practices.
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