Nido Machineries
Manager Enterprise Applications, Data & AI
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Mumbai, Maharashtra, India
Work mode:
Onsite
Published on:
30 September 2026
What they need
Role mandate
Own NIDOs enterprise application, data and internal AI/automation stack so ERPNext and connected platforms become integrated, trusted and increasingly automated operating systems for the business.
What success looks like
- Stabilise and extend ERPNext around approved business processes and master data.
- Deliver reliable integrations, dashboards and workflow automations.
- Build NIDO AI Hub and My NIDO as governed enterprise capabilities.
- Improve data quality, KPI consistency and user adoption.
- Reduce manual re-entry and fragmented spreadsheet-based workflows.
Key responsibilities
- Own ERP Next functional/technical roadmap, configuration governance, enhancements and release/UAT process.
- Own integrations/APIs between ERP Next, Jira, Microsoft 365/OneDrive, web/forms and other enterprise systems.
- Own enterprise data models, BI dashboards, KPI/PMS technology and trusted reporting layers.
- Lead NIDO AI Hub / My NIDO internal AI use cases, prompt/workflow governance and safe enterprise adoption.
- Manage ERP/business analysts, data/BI capability and API/automation/full-stack engineering as team develops.
- Maintain system documentation, master-data rules, role/access design with Cybersecurity and adoption/training.
- Translate functional requirements into scalable system design; challenge unnecessary customisation.
Ideal candidate profile
Business-systems leader/solution architect with strong ERP, integration, data and automation experience. Must understand business processes deeply enough to avoid simply automating bad processes.
Experience & qualifications
- 814+ years enterprise applications/ERP experience.
- ERPNext/Frappe strongly desirable; strong experience with another ERP acceptable if candidate can adapt quickly.
- API/integration, SQL/data modelling, BI and workflow automation knowledge.
- Exposure to LLM/AI enterprise workflows useful; production governance more important than hype.
- Manufacturing/project/service processes preferred.
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