Data Analytics Engineer

California State University, Northridge is hiring a Data Analytics Engineer to develop, maintain, and support data engineering, integration, reporting, and analytics solutions for academic and administrative operations. The role builds data pipelines and analytics-ready datasets, maintains data quality controls, and develops dashboards and reporting solutions.

Responsibilities

Designs, develops, tests, deploys, and maintains ETL/ELT data pipelines, APIs, integrations, scripts, and scheduled data processes

Implements data validation, monitoring, logging, error handling, and reconciliation controls to improve accuracy, completeness, reliability, and recoverability

Develops, enhances, and maintains dashboards, reports, visualizations, certified datasets, and related analytics solutions using approved platforms such as Tableau, Power BI, and QuickSight

Develops and supports data services and pipelines used by workflow automation, advanced analytics, and approved AI-enabled solutions

Translates defined requirements into technical specifications, data mappings, process flows, test plans, and implementation tasks

Performs other duties as assigned

Preferred

degree in Computer science, Data Analytics, Data Science, Information Systems or a related field is preferred

Experience with statistical analysis, predictive modeling, machine learning, or data science methods is desirable

Computer Science

Data Analytics

Data Science

Information Systems

Statistical Analysis

Predictive Modeling

Machine Learning

Data Science Methods

Benefits

Medical

Dental

Vision

Retirement & savings

Tuition waiver

The position is currently hybrid (3 days in office, 2 days remote); however, this is subject to change based on student and/or operational needs.

Company

Public university serving students and community in Los Angeles

Northridge, California, USA

https://www.csun.edu/

Founded in 1958

1001-5000 employees

Qualifications

Equivalent to a bachelor's degree in a related field and two years of relevant experience

Additional experience which demonstrates acquired and successfully applied knowledge and abilities shown above 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

Comprehensive knowledge of data engineering principles and practices, including ETL/ELT pipelines, APIs, data modeling, data transformations, cloud and SaaS data environments, data warehouses, lakes, and lakehouse platforms, with demonstrated skill in developing scalable, reliable, and maintainable data solutions

Strong analytical and technical problem-solving skills with the ability to troubleshoot data pipelines, integrations, performance issues, and data anomalies; implement data quality and governance controls; and collaborate effectively with technical and functional partners to coordinate dependencies and deliver data-driven solutions across systems and platforms

Thorough knowledge of reporting and analytics principles, with demonstrated skill in developing dashboards, reports, visualizations, certified datasets, reporting structures, and semantic layers using platforms such as Tableau, Power BI, and QuickSight; ability to validate data, metrics, calculations, and outputs and resolve reporting accuracy, usability, and performance issues

Ability to gather and translate data, reporting, integration, and automation requirements into technical specifications, mappings, process flows, test plans, and implementation tasks; evaluate emerging technologies, support advanced analytics and AI-enabled solutions, and produce clear technical documentation while applying established accessibility, security, privacy, architecture, and data governance standards

Applicants must be authorized to work for any employer in the United States

Degree in Computer science, Data Analytics, Data Science, Information Systems or a related field is preferred

Experience with statistical analysis, predictive modeling, machine learning, or data science methods is desirable

Additional experience which demonstrates acquired and successfully applied knowledge and abilities shown above 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.

Required skills

Data Engineering, ETL/ELT Pipelines, APIs, Data Modeling, Cloud and SaaS Data Environments, Data Warehousing, Data Lakes and Lakehouse Platforms, Tableau, Power BI, Amazon QuickSight, Data Governance, Machine Learning

Experience

2+ years