Senior Data Analytics Solutions Architect

CSUN strives to be a destination workplace, where everyone understands that they belong to a community that is vital in advancing student success and providing exemplary service to all stakeholders. We foster an environment of success, both for our students and our employees. We have a relentless passion for celebrating diversity, equity, and inclusion as well as being an employer of choice. You will also have the opportunity to realize your own personal goals and be recognized for the work you do, and enjoy the unique value the CSUN community can offer. If this sounds like you, you’ve come to the right place. Learn more: https://www.csun.edu/about-csun.

 

Major Duties

Under general supervision, the Senior Data Analytics Solutions Architect provides advanced technical expertise across data architecture, analytics, and automation. This role partners with campus stakeholders to translate complex business needs into scalable, secure, and governed data solutions, independently designing and delivering integrations, analytics, and reporting capabilities aligned with enterprise standards.

Key Responsibilities

Data Architecture and Solution Design

• Translate business requirements into technical specifications, data models, process maps, and documented end‑to‑end data solutions
• Design scalable data architectures that support analytics, reporting, and automation use cases across campus systems

 Data Integration and Engineering

• Design and implement ETL pipelines, APIs, and data integrations across institutional platforms, including ServiceNow
• Ensure solutions align with data governance, security, and enterprise integration standards

 Analytics and Reporting

• Develop and maintain complex dashboards, visualizations, and reporting solutions using institutionally selected platforms such as Tableau, Power BI, and Amazon QuickSight
• Partner with functional teams to ensure analytics solutions are actionable, accurate, and aligned with decision‑making needs

Data Quality and Operational Excellence

• Implement data quality checks, monitoring, and validation processes to ensure accuracy, completeness, and consistency across datasets
• Troubleshoot and resolve complex data and integration issues across systems

Innovation and Technical Advisory

• Evaluate and pilot emerging technologies and analytics approaches
  Provide technical recommendations and architectural guidance to department leadership to inform future investments and strategy
• Perform other duties as assigned

*NOTE: To view the full position description, including all of the required qualifications, copy and paste this link into your browser:  https://mycsun.box.com/s/97zib9u6ny7c5hrv8dxxv6b8nfkp5i5x 

 

Qualifications

• Equivalent to a bachelor’s degree in a related field and five years of relevant experience.
• Additional experience which demonstrates acquired and successfully applied knowledge and abilities shown below, may be substituted for the required education on a year-for-year basis.
• An advanced degree in a related field may be substituted for the required experience on a year-for-year basis. 

 

Preferred Qualifications:

• Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Data Science.
• Hands-on & progressively responsible experience in data architecture, data engineering , and analytics.
• Skilled programmer, experienced in modern programming and query languages (e.g., C#, Python/PySpark, Java, SQL) to support development, data transformation, analytics, automation and system integration is a plus.
• Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making.
• Demonstrated experience designing and implementing ETL/ELT pipelines using modern SAAS or cloud Integration platforms (e.g., Boomi, Talend, AWS Glue, Azure Data Factory etc.,) .

 

Knowledge, Skills, & Abilities

• Demonstrated experience in business process design and optimization, in data-intensive environments. 
• Proven ability to translate business and analytical requirements into technical specifications, data models, integration logic, and analytics-ready data solutions. 
• Expert knowledge of data modeling, statistical