Data Analytics Developer II

Data Analytics, Data Science, System Design, & Development

• →Design, develop, and maintain data analytics solutions, data models, statistical analyses, reports, dashboards, and data products that support institutional research, operational analysis, student success initiatives, enrollment planning, compliance reporting, and data-informed decision-making.
• →Apply data science, data mining, statistical, and machine learning methods to identify trends, patterns, relationships, anomalies, and predictive indicators within institutional datasets.
• →Conduct moderately complex data analysis, including descriptive statistics, trend analysis, cohort analysis, segmentation, predictive modeling, forecasting, classification, and optimization techniques, under general supervision.
• →Develop, test, and maintain predictive or analytical models to support business and institutional needs, including models related to student outcomes, enrollment trends, retention, graduation, course demand, operational performance, or other institutional priorities.
• →Prepare, clean, transform, normalize, and integrate large and diverse datasets from multiple systems to support statistical analysis, machine learning, reporting, and visualization.
• →Design and develop data pipelines, extract-transform-load processes, data integrations, and automated workflows that support analytics, reporting, institutional research, and business intelligence needs.
• →Gather and document functional and technical requirements by working with stakeholders to clarify objectives, data definitions, analytical questions, data sources, dependencies, assumptions, limitations, and expected deliverables.
• →Translate business and research questions into data requirements, analytical approaches, model specifications, reports, dashboards, or data solutions.
• →Create and maintain relational or dimensional data models for institutional data, including student, course, finance, human resources, learning management, and other administrative data.
• →Develop and maintain SQL scripts, queries, stored procedures, database objects, data extracts, APIs, connectors, or other technical solutions to support data access, analysis, integration, and reporting.
• →Write, review, test, and maintain code used to process, analyze, transform, model, and visualize complex datasets using relevant programming languages, statistical tools, business intelligence platforms, or data analytics frameworks.
• →Build dashboards, reports, visualizations, and analytical summaries that communicate findings clearly to technical and non-technical stakeholders.
• →Document analytical methods, model assumptions, data definitions, source-to-target mappings, validation logic, business rules, technical specifications, and process workflows to support transparency, reproducibility, and maintainability.
• →Evaluate data for completeness, accuracy, reliability, bias, and appropriate use; identify data limitations and communicate findings, caveats, and risks to stakeholders.
• →Implement data validation rules, quality checks, reconciliation processes, and error-handling procedures to support accuracy and consistency of institutional datasets used for reporting and analysis.
• →Contribute to the selection, testing, and implementation of data analytics tools, methods, scripts, models, and workflows that improve efficiency, scalability, and analytical capability.
• →Collaborate with Institutional Research, Information Technology, academic and administrative units, and other campus stakeholders to develop customized data analytics solutions that support university goals and objectives.
• →Contribute to project planning by estimating assigned tasks, tracking progress, documenting activities, identifying issues or variances, and communicating status updates to managers, project leads, and stakeholders.
• →Provide technical guidance, training, and support to users, student assistants, or less-experienced staff on assigned analytics tools, reports, datasets, procedures, and data interpretation.

Operational Support, Data Quality, & Reporting Support

• →Provide operational support for data analytics systems, data pipelines, databases, reports, dashboards, models, scheduled jobs, and recurring analytical processes.
• →Monitor scheduled data loads, reporting processes, analytical workflows, and integrations; identify data or process issues; and resolve routine to moderately complex errors.
• →Troubleshoot and resolve data, query, report, integration, model, and system issues using standard database languages, statistical tools, business intelligence platforms, or programming languages.
• →Develop, modify, and optimize SQL scripts, queries, reports, data extracts, and analytical workflows to resolve user-reported issues and support evolving business requirements.
• →Support database and analytics environments, including Microsoft SQL Server, Oracle, MySQL, data warehouse platforms, reporting tools, or related systems, by assisting with performance monitoring, indexing, permissions, configuration, and data integrity activities.
• →Debug and improve code, scripts, reports, dashboards, data models, and automated processes to enhance accuracy, reliability, usability, and performance.
• →Support compliance and institutional reporting by preparing, validating, reconciling, documenting, and maintaining data used for university, systemwide, state, federal, accreditation, or other reporting requirements.
• →Ensure assigned work complies with FERPA, data privacy standards, data governance policies, information security requirements, accessibility expectations, and university procedures.
• →Analyze data for quality issues, completeness, inconsistencies, outliers, and anomalies; document findings; and recommend or implement corrective actions as appropriate.
• →Maintain data dictionaries, technical documentation, user guides, process documentation, report specifications, model documentation, and business rules related to assigned systems and analytics processes.
• →Assist with PeopleSoft, enterprise application, data warehouse, institutional reporting, and business intelligence support by researching data issues, validating logic, and providing technical assistance to functional and technical users.
• →Participate in meetings involving data requirements, reporting changes, procedural updates, analytics requests, or system modifications; provide technical input and assist with review and validation of specifications.
• →Provide customer-focused support to campus users by responding to inquiries, explaining data processes, clarifying report logic, resolving assigned tickets, and escalating complex matters when appropriate.
• →Maintain confidentiality and appropriately handle sensitive institutional, student, employee, financial, operational, and research-related data.

• Prior experience supporting CSU ERS/ADPB reporting processes.
• Experience using statistical, data science, business intelligence, or analytics tools to support reporting, forecasting, predictive modeling, or institutional analysis.
• Experience with enterprise administrative systems, data warehouses, reporting tools, analytics platforms, or business intelligence environments.
• Experience developing SQL queries, reports, dashboards, data integrations, automated validation processes, or analytical models.
• Experience with student success, enrollment, retention, graduation, course demand, workforce, finance, or operational analytics.
• Demonstrated skills in an institutional/educational environment possessing a customer-oriented and service-centered attitude.

Back to search results Apply now Refer a friend

• Regular and reliable attendance is required.
• Strong knowledge of data manipulation, transformation, cleaning, validation, integration, and analysis using advanced relevant programming languages, libraries, tools, or frameworks.
• Strong programming skills in relevant languages used for data analytics, statistical analysis, data processing, database development, visualization, integration, and automation.
• Working knowledge of data modeling, statistical analysis, machine learning concepts, predictive modeling, forecasting, classification, clustering, and optimization techniques.
• Ability to apply data science and data mining methods to identify trends, patterns, anomalies, and insights from large and complex datasets.
• Ability to develop reports, dashboards, visualizations, analytical summaries, and data products using business intelligence or data visualization tools.
• Proficiency with data quality management practices, including validation, reconciliation, completeness checks, error handling, anomaly detection, and documentation.
• Understanding of metadata management concepts, data governance practices, data privacy requirements, data security protocols, and appropriate use of sensitive information.
• Strong analytical and problem-solving skills to develop data models, troubleshoot data issues, evaluate data limitations, and draw insights from institutional datasets.
• Ability to gather, interpret, and document business, technical, and analytical requirements and translate them into data specifications, reports, models, integrations, dashboards, or analytics solutions.
• Ability to communicate analytical findings, model assumptions, data limitations, and technical information clearly and concisely to audiences with varying levels of technical knowledge.
• Strong project planning and time management skills to plan, prioritize, and coordinate multiple assignments with fluctuating and time-sensitive deadlines.
• Strong attention to detail and accuracy.
• Skill in providing technical guidance, training, or support to users, student assistants, or less-experienced staff on assigned projects, reports, datasets, or analytical processes.
• Familiarity with data operations principles such as testing, ongoing integration, delivery, automation, documentation, reproducibility, and iterative process improvement.
• Knowledge of or ability to learn database systems including Oracle, Microsoft SQL Server, MySQL, or related platforms.
• Development skills including proficiency with or ability to learn relevant enterprise tools and technologies, which may include Integration Broker, PeopleTools, PeopleCode, Application Designer, Application Engine, Application Packages, Component Interfaces, Configuration Manager, SQL/SQR, XML Publisher, and related systems.
• Ability to create business process guides, user documentation, technical documentation, model documentation, data dictionaries, and process workflows.
• Demonstrated customer service experience requiring a very high level of diplomacy and professionalism.
• Ability to use tact and diplomacy to effectively handle a broad range of high level and sensitive interpersonal situations with diverse personalities, and to respond appropriately to conflicts and problems.
• Ability to initiate, establish, and foster communication and teamwork by maintaining a positive, cooperative, productive work atmosphere in the University with the ability to establish and maintain effective working relationships within a diverse population and with those from various cultural backgrounds.
• Excellent communication skills; ability to effectively communicate information in a clear and understandable manner.
• Thorough knowledge of English grammar, spelling, and punctuation.
• Ability to interpret, communicate and apply policies and procedures.
• Ability to maintain a high degree of confidentiality.
• Excellent organizational and time management skills with the ability to set own priorities to coordinate multiple assignments with fluctuating and time-sensitive deadlines.
• Excellent computer skills and competence with a variety of computer applications including word-processing, spreadsheets, databases, on-line systems, Internet as well as online calendaring and email.
• Working knowledge of or ability to quickly learn University infrastructure.
• Must be willing to travel and attend training programs off-site for occasional professional development.
• Must be able to work occasional holidays and adjust working hours to meet special jobs. May be called back periodically to perform work as needed on an emergency basis.