DATA501: Data Intelligence Stack Owner

JerseySTEM, Inc.

3d • Remote

About The Position

This is a pro-bono volunteer position.
JerseySTEM is seeking an AI-Forward Data Intelligence Stack Owner to lead the evolution of our data-to-intelligence pipeline. The scope of this role is strictly focused on the Intelligence Layer of the tech stack, transforming organizational data into automated insights
You will architect a stack that leverages Generative AI, Automated Data Pipelines, and Predictive Modeling to provide real-time, actionable intelligence. You are the bridge between raw data silos and an AI-enhanced decision-making culture.

Requirements

• Applied AI for Analytics: Strong understanding of how to use LLMs specifically for data extraction, SQL generation, and automated synthesis
• Modern Data Stack Expertise: Experience with cloud data warehouses and AI-integrated BI tools (e.g., Looker’s Duet AI, Power BI Copilot).
• Data Engineering Mindset: Proficiency in SQL and Python, with an emphasis on building clean data for AI consumption.
• Visionary Thinking: Ability to replace spreadsheets with automated, intelligent solutions.
• Ability to translate AI-driven outputs simply to cross-functional partners.
• Comfortable working in a remote, distributed, member-driven environment.
• Minimum commitment of 6 hours per week.

Nice To Haves

• Experience building data products, automated reporting agents.
• Previous experience in a leadership role within a tech-focused nonprofit or startup leading through shifts from legacy to automated data ecosystems.
• Familiarity with "AI-as-a-Service" platforms and low-code AI automation.
• Retired professionals or those seeking meaningful pro bono work are welcome.

Responsibilities

• AI-Centric Architecture: Design and oversee a data stack (Google BigQuery, Vertex AI, or similar) that prioritizes AI readiness and automated data flow.
• Generative Insights: Implement AI "Chat-with-your-Data" interfaces and LLM-driven summarization for stakeholders to interact with organizational data.
• Predictive Analytics: Move beyond historical reporting to build models that predict volunteer churn, student engagement trends, and fundraising opportunities.
• Automated Governance: Utilize AI tools to monitor data quality, flag anomalies, and ensure privacy compliance automatically.
• Orchestration: Integrate data from platforms (Salesforce, Jira, Google Workspace) using AI-friendly ETL/ELT processes that minimize manual intervention.
• Implementation: Directly configure and code/test the initial data pipelines, AI integrations, and reporting logic before scaling through the lean team."
• Team Leadership: Recruit and mentor a "Lean Data Team" focused on modern techniques like prompt engineering for data, automated visualization, and data engineering.

What This Job Offers

• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 11-50 employees