About Neon One

Neon One has been a leader in nonprofit software since 2004, building intuitive tools that help small and mid-sized nonprofits connect with people, build trust, and make good happen every day. The culture runs on empathy, innovation, and a shared mission to empower organizations driving real-world impact.

About the Role

Neon One is looking for a foundational member of its data team to architect the data models and intelligence layer that let AI agents automate business processes across its products. This is a greenfield opportunity — you’ll work with rich, diverse datasets across the product ecosystem, building core data layers and intelligent systems from the ground up to power autonomous decision-making and automated reporting.

What You’ll Do

• Design relational, dimensional, and analytical data models from large, disparate datasets, and extend them into Salesforce Data 360 for optimal downstream analytics and Agentforce AI agents
• Partner with the Data Engineer and Salesforce architects on data requirements, pipeline integrity, schema design, and zero-copy data federation between Snowflake/AWS and enterprise CRM systems
• Design, build, train, and validate machine learning models, with a focus on packaging, deploying, and monitoring them in production at scale
• Transform complex model outputs into production-ready data products, and communicate architecture decisions to technical and executive audiences alike
• Develop the data layers and infrastructure that power reports and dashboards, delivering insight at both an aggregate and per-customer level

What You’ll Bring

• 4+ years of hands-on experience in a data science or data engineering role, with a track record of building data models and deploying ML infrastructure in production
• Strong Python proficiency for data manipulation, ETL/ELT processes, and system integration
• Hands-on experience building, training, and deploying ML models on a major cloud platform; AWS SageMaker experience highly preferred
• Advanced SQL skills and a deep understanding of data warehousing, dimensional modeling (Kimball), and schema design for ML pipelines
• An autonomous, self-starter mindset comfortable with ambiguity and end-to-end ownership
• Exceptional communication skills across technical and non-technical audiences
• A Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related quantitative field

Bonus Points

• A Master’s or Ph.D. in Computer Science or a related technical field
• Direct experience architecting within Snowflake (Streams, Tasks, or Snowpark)
• Experience with Salesforce Data Cloud (Data 360), Mulesoft, or data structures built for autonomous AI agents (Agentforce)
• NLP experience or engineering pipelines for LLMs and vector databases
• Familiarity with multi-tenant databases or data isolation in a SaaS environment
• Prior experience with, or a passion for, the non-profit sector