"Data Engineer"
: Job Details :

Title: Data Engineer Client: University of Maryland Global Campus Duration: 1 Year Any visa is fine Work Location: Hybrid. 3 days and 2 days remote. Local resources are highly preferred. Address: University of Maryland Global Campus 3501 University Boulevard East Adelphi, Maryland 20783 • Must have experience with AWS, Python, APIs, and other ETL tools • Provide a daily load of system data into the data warehouse environment including resolution of connection and job process failure issues. Provide on-call support for daily loads with appropriate communication/escalation as necessary. • Coordinate with IT and platform teams on updates/changes to source systems (Peoplesoft, Salesforce, etc.) that impact data warehouse data, including testing of major releases of source systems for impact to data warehouse reporting. • Maintain and enhance existing data integrations with key source systems to include SIS (PeopleSoft), CRM (Salesforce & Marketing Cloud), LMS (D2L), Workday, Marketing data feeds, Institutional Advancement (Ellucian Advance), and others. • Evaluate, scope, and deploy new or migrate existing data integrations as needed. • Provide daily extracts of data for ingestion of data warehouse data into other internal or external systems to include CRM (Salesforce), Assessment, Marketing vendors, and others. • Course Evaluation Data Integration - provide daily data availability for prompt delivery of course evaluations surveys delivered by a third-party survey tool. • Consume results of evaluations into performance reporting. • Provide ongoing data warehouse and data modeling design to maintain the platform and respond to evolving business needs. Maintain data lake repository for storage of transactional data from source systems. • Maintain star schema data models to support business needs and efficiency of data solutions and tools. • Maintain metadata layer of the data warehouse optimizing ease of use for end users. Prioritize daily refresh of the reporting layer based on source data availability and end user needs. • Perform required updates to include changes in definitions, new fields added to existing systems, and new aggregations to support alternative forms of analysis. • Troubleshoot issues that are identified within existing and new data models in partnership analysts or business contact.