Data Architect III

Position Highlights Please note: This posting has been updated in its Position Highlights section. Developer, Extract Transform Load/ETL (Data Architect III) position will primarily focus on designing, developing, and implementing the ETL/ELT processes for the PeopleSoft and Kuali contents of the data warehouse. The incumbent in this position will work with subject matter experts and Business Intelligence Analysts to transform business requirements and deliver the data warehousing and business intelligence components essential for decision making. This position will also assist in the design, development and implementation of dimensional models, or other similar data structures as needed., * Develop, test and maintain IBM InfoSphere DataStage 11.7 jobs for the institutional Data Warehouse.

• Participate in the development of coding standards for IBM InfoSphere DataStage.
• Act as an ETL consultant for other areas or teams.
• Develop AWS Glue jobs for the ETL/ELT Processes as part of the Datawarehouse Modernization Initiative.
• Develop and maintain reports and dashboards as needed.
• Assist in supporting the nightly jobs already in production at the University.
• Provide input and support for upgrades, capacity planning, and "best practices".
• Assist with deployment of data models in the Oracle Business Intelligence Enterprise reporting tool.
• Creating and maintaining documentation relating to business processes translated into ETL/ELT jobs.
• Performance Tuning of the ETL/ELT Processes.
• Gathering and analyzing business, data and reporting requirements, plus documentation and specification of requirements.

Applicants must be currently authorized to work in the United States., * Working knowledge with ETL/ELT platforms with IBM InfoSphere DataStage and AWS Glue.

• Ability to design, implement, and troubleshoot ETL/ELT jobs.
• Knowledge of scheduling tools to schedule ETL/ELT jobs.
• Knowledge of best practices in structured and unstructured databases, ETL design, and/or BI technologies.
• Knowledge in database modeling techniques and best practices such as Star, Snowflake, 3NF, etc.
• Ability to communicate complicated technical knowledge in a way that non-technical data roles will be able to understand.
• Excellent interpersonal and communication skills, both written and verbal.
• Demonstrated productivity when working independently and as a team member.
• Ability to work in a highly collaborative and inclusive environment.
• Ability to multi-task and meet negotiated deadlines.
• Demonstrated knowledge of Higher Education PeopleSoft HCM and CSW modules.
• Demonstrated knowledge of Higher Education Kuali Financial and Kuali Coeus modules.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve., * Bachelor's degree or equivalent advanced learning attained through professional level experience required., * Minimum of 5 years of relevant work experience, or equivalent combination of education and work experience., * Four or more years of experience creating jobs in IBM InfoSphere DataStage ver. 9+

• Two or more years of experience creating AWS Glue ETL/ELT jobs
• Work experience with AWS Cloud services like Glue, S3, Redshift, Athena, Lambda, Step Functions, AppFlow, Cloud Formation and Code Pipeline
• Three or more years of experience with Oracle RDBMS
• One or more years of experience with PeopleSoft EPM
• Experience using Control-M to schedule Datastage jobs and AWS Glue jobs
• Work experience in human resources, financial and/or student system column definitions
• Experience with Oracle Business Intelligence Enterprise Edition Reporting and Visualization tools
• Experience with ERP data structures and how they relate to establishing data warehousing, data management, and analytics architecture
• Experience developing business requirements and translating them into a data warehouse dimensional model