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11 дней назад

Business Systems Architect / Integration Lead (Manufacturing Systems)

175 000 - 200 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior/lead
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Business Systems Architect / Integration Lead (Manufacturing Systems): Leading contract manufacturing integrations and governed manufacturing data products across enterprise systems, Microsoft Azure, and Microsoft Fabric with an accent on transaction reliability, data standardization, and operational visibility. Focus on defining integration patterns, mapping manufacturing transactions, building reconciliation and observability processes, and enabling trusted production, inventory, quality, and shipment analytics.

Location: Fremont, California, USA

Annual salary: $175,000–$200,000, plus bonus and equity eligibility.

Company

hirify.global develops integrated clean-energy technology for utility-scale solar power plants, combining structural, electrical, digital, data-driven, and automation solutions.

What you will do

  • Own the product vision, roadmap, backlog, and delivery priorities for contract manufacturing systems integration and manufacturing data products.
  • Lead onboarding and integration of contract manufacturing partners through APIs, file exchanges, batch processes, event-driven flows, and other connectivity methods.
  • Define transaction mappings, validation, reconciliation, error handling, alerting, replay, support procedures, and partner operating standards.
  • Shape a governed manufacturing data foundation using Microsoft Azure and Microsoft Fabric, including OneLake, Lakehouse, Data Warehouse, Data Factory, semantic models, and Power BI.
  • Enable trusted operational dashboards and analytics covering production, materials, inventory, quality, yield, cycle time, throughput, delivery, and exceptions.
  • Lead cross-functional delivery from discovery through testing, deployment, stabilization, production support, and continuous improvement.

Requirements

  • Bachelor’s degree in information systems, computer science, engineering, supply chain, manufacturing, business, or a related field.
  • 8+ years of experience in enterprise systems, product management, systems integration, supply chain technology, manufacturing technology, data platforms, or a related discipline.
  • Experience owning technology products or capabilities from business discovery through delivery and ongoing operations.
  • Strong understanding of manufacturing, supply chain, inventory, quality, procurement, logistics, enterprise transactions, data mappings, validation, reconciliation, and data-quality controls.
  • Working knowledge of Microsoft Azure and Microsoft Fabric data services, including OneLake, Lakehouse, Data Warehouse, Data Factory, SQL, data modeling, and Power BI.
  • Ability to collaborate with engineers, architects, developers, analysts, business users, vendors, contract manufacturers, and executive stakeholders.

Nice to have

  • Experience with Microsoft Fabric implementations, MES, ERP, PLM, QMS, WMS, TMS, or supplier portals.
  • Knowledge of ISA-95, OEE, manufacturing quality processes, factory data models, traceability, genealogy, WIP, yield, defects, rework, and test results.
  • Experience with Azure Data Factory, API management, event-driven integration, T-SQL, PySpark, Python, lakehouse design, semantic models, monitoring, security, and CI/CD.
  • Experience with data governance, master data management, lineage, data contracts, observability, global partner onboarding, or plant rollouts.

Culture & Benefits

  • Full-time employment within a global clean-energy technology organization.
  • Bonus and equity eligibility are included in the total compensation package.
  • Work involves collaboration across manufacturing partners, operations, supply chain, finance, quality, technology, and analytics teams.
  • Focus on reliable production systems, governed data, operational visibility, and future AI use cases.

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