Data and Business Systems Engineer, Open Farm

• 4+ years of hands-on experience in data engineering, analytics engineering, or a business systems role with a significant data component
• Strong SQL proficiency for data extraction, transformation, and reporting
• Hands-on experience building ELT/ETL pipelines with dbt or equivalent
• Experience with NSAW or Snowflake for data modeling and reporting; both is a strong plus
• Working proficiency in Python for scripting, automation, and pipeline development
• Substantial experience designing and building integrations using REST APIs and webhook-based patterns, including authentication and end-to-end delivery
• Practical experience using AI/LLM tools in a development or business workflow
• Ability to work independently as a primary technical resource and deliver without close oversight
• Clear written and verbal communication, including translating technical decisions into plain language for business stakeholders

Desirable

• Open Farm's data currently lives across NetSuite, NSAW, Shopify, and Salsify, with too much of the business still running on manual spreadsheet tracking
• That is the problem you would be solving
• We are looking for a Business Systems Data Engineer to build the data infrastructure that gives the business consistent, reliable reporting
• This is a full-time internal role reporting to the IT Director
• You will be the primary technical owner of our data pipelines, data models, and reporting layer relied on by Operations, Finance, and eCommerce, with a strong secondary focus on connecting our platforms through API-based integrations
• AI tooling is a core part of how this role operates, not an afterthought
• Build and maintain ELT pipelines moving data from NetSuite, Shopify, Salsify, and other source systems into the reporting environment
• Develop and maintain data models, workbooks, and SuiteAnalytics reports in NSAW as the primary near-term reporting layer
• Apply data transformation practices (dbt or equivalent) to keep logic version-controlled, tested, and documented
• Replace manual spreadsheet-based tracking with system-driven, auditable data flows
• Document data models, pipeline logic, and reporting structures clearly for stakeholders and future developers
• Platform Connectivity and Integrations
• Design and build integrations connecting Open Farm's platforms, with the data warehouse as the central hub
• Develop and consume REST APIs and webhook-based integrations with proper authentication (OAuth 2.0, API keys, tokens), error handling, retry logic, and monitoring
• Manage and troubleshoot existing integration pipelines built on Celigo and NetSuite Oracle Integrator (NSIP)
• Replace fragile FTP and CSV-based data exchanges with direct, auditable system-to-system connections
• Maintain and extend existing integrations between NetSuite and Shopify, Salsify, EDI partners, and WMS
• ERP Working Knowledge
• Read, troubleshoot, and make minor modifications to existing configurations and scripts within the organization's ERP (currently NetSuite); basic literacy required, advanced development is owned by another team member
• Build and maintain saved searches and reporting workbooks within the ERP to support reporting needs
• Understand the ERP's core data model in sufficient depth to model it accurately downstream
• AI-Driven Automation
• Use Claude, Claude Code, and equivalent tools as active components of the development workflow
• Build API-level integrations with LLM services to embed AI capability into data workflows and broader business processes
• Identify manual, repetitive processes across the business that are strong candidates for AI-assisted automation and develop the solution
• Apply a practical, grounded approach to AI adoption that accounts for both capabilities and limitations
• Development Practices
• Write clean, maintainable, well-documented SQL and Python for data pipeline and automation work
• Manage all code through Git/GitHub including branching, pull requests, and documented change history
• Write unit and integration tests as a standard part of development
• Respond to data and pipeline issues with urgency and structured troubleshooting