Data Warehouse & Integration Architect

The Division of Information Technology (it.gwu.edu) is the chief provider of technology infrastructure, services and applications at GW. The Division partners with stakeholders across GW to equip students, staff and faculty with the technology know-how and tools necessary to achieve academic excellence. Reporting to the Assistant Director of Data Warehouse & Integration, the Data Warehouse & Integration Architect works primarily within the Division’s Business Intelligence and Enterprise Information Services Department and other units as needed.

The Data Warehouse & Integration Architect is responsible for undertaking multiple engagements, working with different teams and business stakeholders, focusing on multiple aspects of data architecture, data initiatives, data projects and data integrations. The Architect manages technical dialogues with clients from multiple business lines within the organization to define industry best practices and implement solutions architecture for the University Data Warehouse and enterprise data integrations. The Architect works with technology and strategy groups within GW to facilitate design and development discussions and then implements those strategies in as a member of a SCRUM Agile team.

Key activities include:

• Conducts enterprise architectural design, business analysis, data modeling, and implementation of the University’s data warehouse initiative. Coordinates with various user groups to gather and analyze requirements and promote the correct interpretation and use of data warehouse information. Works with business users, application developers, and database administrators to map business requirements into conceptual, logical, and physical models while ensuring conformance of all design and analytical deliverables to enterprise standards. Instructs (or Educates) business and technical users in interpreting and applying laws and policies governing protection of confidential, sensitive, and proprietary information.

• Conducts the enterprise architectural design, business analysis, data modeling, and implementation of the University’s data integration platform initiative. Coordinates with various user groups to gather and analyze requirements and promote the correct interpretation and integration of University information. Works with business users, application developers, and database administrators to map business requirements into working integrations while ensuring conformance of integrations to enterprise standards. Instructs (or Educates) business and technical users in interpreting and applying laws and policies governing protection of confidential, sensitive, and proprietary information.

• Enhances and maintains a repository of cross-referenced metadata of information requirements, data definitions, data relationships, naming and formatting standards, and stakeholder organizations to be used for impact analysis, change management purposes, and to support new application development.

• Identifies data quality issues related to integration of shadow systems into GW’s Enterprise Applications and development of new applications. Researches and recommends software tools for data cleansing. Provides leadership in coordinating various stakeholder groups to improve the accuracy and completeness of GW’s enterprise data. Researches and recommends software tools for application development life-cycle support. Identifies, documents, and publicizes information on University stewards and/or organizations responsible for defining data elements and quality. Develops metrics to monitor data quality.

• Develops training material and deliver training for data warehouse deliverables. Sets strategies and implements related activities to enhance data quality as data from multiple systems are consolidated. Promotes the creation and use of data management best practices within the business and technical community. Supports an enterprise-wide view of University data and serves as a facilitator to mediate data management issues. Participates in and supports activities of the University’s data standards committee, recommends and documents standard definitions and formats; and disseminates data standards to business users and technical personnel.

• Enhances professional knowledge and skills by attending conferences and advanced training in required areas of expertise

The position is based at GW’s Virginia Science & Technology campus in Ashburn, VA but may require travel to the Foggy Bottom campus located in Washington, DC. The incumbent may perform other related duties as assigned. The omission of specific duties does not preclude the supervisor from assigning duties that are logically related to the position.

Qualified candidates will hold a Bachelor’s degree in an appropriate area of specialization plus 7 years of relevant professional experience, or, a Master’s degree or higher in a relevant area of study plus 5 years of relevant professional experience. Degree must be conferred by the start date of the position. Degree requirements may be substituted with an equivalent combination of education, training and experience.

• Experience owning end-to-end data analysis, modelling and development tasks for at least 3 to 4 very large data integration or warehousing projects.

• Data modeling experience building enterprise data models for multiple purposes (conceptual, logical and physical) such as Star Schema, Operational Data Store, Graph

• Database design, application design/development, and hands on programming experience in: Database Tables, Graph Nodes and Relationships, JSONSchemas

• Experience with ETL technologies and data movement for various purposes: The University Data Warehouse, The University Operational Data Store/Data Lake, NoSQL/Graph, Application Integration

• Data integration and data delivery experience in: Flat file Creation and Distribution, API Development and Management, Hosted Direct SQL

• Data visualization and analytics experience in: Dashboard development, Search based analytics, Predictive analytics

• Strong familiarity with:

  • Data Architecture best practices (including approaches, related tools, design best practices, standards and principles)

  • Data Warehousing Solution Architecture 

  • Database tuning and data application optimization

  • Big-Data concepts

• Business process analysis, project management, stakeholder management experience.

• Exceptional communication skills