Data Integration Developer

Sulphur Springs Valley Electric Cooperative•, AZ

1d•Hybrid

About The Position

The Data Integration Developer designs, develops, and maintains enterprise data integrations, reporting solutions, analytics platforms, and AI-ready data environments. This position transforms complex data into reliable, accessible, and actionable information that supports reporting, forecasting, automation, performance measurement, and data-driven decision-making throughout the Cooperative. The role also serves as a lead coordinator for enterprise data and analytics initiatives, working with departments, system owners, vendors, and technical teams to improve data quality, governance, accessibility, and reporting capabilities.

Requirements

Bachelor's degree in a related field and 3-5 years of directly related experience, or an equivalent combination of education and experience.
Experience developing data pipelines, models, dashboards, and enterprise reporting solutions that support data governance, quality, analytics, and AI initiatives.
Strong analytical, statistical, problem-solving, and data interpretation skills.
Ability to communicate technical information and collaborate effectively with cross-functional teams.
Candidates must be able to obtain a valid Arizona Driver's License and successfully complete standard pre-employment drug screening and background checks.

Nice To Haves

Microsoft Azure Data Engineer, Microsoft Power BI, Security+ or other enterprise data or analytics platform certifications

Responsibilities

Design, develop, maintain, and optimize data pipelines from enterprise systems.
Develop standardized data models, dashboards, reports, metrics, and analytical solutions.
Integrate enterprise data across operational, financial, GIS, engineering, and enterprise systems.
Maintain data quality through validation controls, reconciliation processes, documentation, and governance standards.
Collaborate with departments and technical teams to resolve data, reporting, and system integration issues.
Develop AI-ready data environments that support automation, forecasting, analytics, and decision support.
Identify opportunities to automate reporting and data processes while providing technical guidance and training on enterprise data and reporting tools.