Data and Business Systems Engineer
Open Farm
| Company | Open Farm |
| Category | Engineering |
| Location | Toronto |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Us
At Open Farm we are transforming the way people feed their pets, with a focus on producing premium, healthy food and treats, all ethically sourced from farm-to-bowl. Headquartered in Toronto and with team members across the US, Open Farm is one of the fastest growing CPG companies in North America. We believe that the best foods are made with consciously sourced, top-quality ingredients from farmers and fisheries who believe in doing good for all animals and the environment. The Opportunity
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.
What You Will Own and Drive
Data Architecture and Engineering
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
What You Bring to the Table
Required
4+ years of hands-on experience in data engineering, analytics engineering, or a bus
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