Global Business Process Owner - Manufacturing Data Platform

Reckitt
Slough
Workplace: OnsiteFull timeFunction: Manufacturing & Production OperationsExperience: 2-5 yearsSkills: ["System thinking","Structured approach","Pragmatism","Communication","Ownership"]

Own the manufacturing data platform and ensure digital manufacturing solutions are built on a coherent, scalable data foundation. You’ll map end-to-end data flows across shopfloor systems, MES/operational systems, ERP (e.g., SAP), and data platforms (e.g., Siemens on AWS), define connectivity and data standards, and translate use cases into data requirements, models, and dependencies. Support governance and PMO decision-making across the global factory network.

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Reckitt
Reckitt
1 day ago

Global Business Process Owner - Manufacturing Data Platform

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Last checked: 6 hours agoStatus: Live

Job Summary

Own the manufacturing data platform and ensure digital manufacturing solutions are built on a coherent, scalable data foundation. You’ll map end-to-end data flows across shopfloor systems, MES/operational systems, ERP (e.g., SAP), and data platforms (e.g., Siemens on AWS), define connectivity and data standards, and translate use cases into data requirements, models, and dependencies. Support governance and PMO decision-making across the global factory network.
Location: Slough
Workplace: Onsite
Employment Type: Full time
Job Function: Manufacturing & Production Operations
Seniority: Mid level

Key Responsibilities

  • •Map and understand end-to-end data flows across shopfloor systems, MES/operational systems, ERP (e.g., SAP), and data platforms (e.g., Siemens on AWS).
  • •Support practical, scalable data architecture aligned across operational systems, cloud platforms, and analytics environments.
  • •Define and enforce data connectivity standards, ingestion logic, naming conventions, and structuring principles across sites and use cases.
  • •Translate digital use cases (e.g., performance management, predictive maintenance) into data requirements, data models, and system dependencies.
  • •Provide visibility into data dependencies, readiness gaps, and risks, and support program governance with structured data-related inputs.

Pay and Benefits

Perks:Parental LeaveHealth InsuranceLife InsuranceEquity

Key Requirements

  • •2–5 years’ experience in a manufacturing/CPG environment and data analytics/data engineering/industrial data.
  • •Exposure to supply chain processes and digital/IT-enabled manufacturing environments.
  • •Hands-on experience with data platforms (e.g., Siemens, Azure, AWS) is a plus.
  • •Degree in Engineering, Data Science, Industrial IT or a related field.
  • •Proficiency in SQL and Python (or similar), with data modelling and data pipelines/APIs, plus system thinking and structured problem-solving.
Experience:2-5 yearsManufacturingCPGData analyticsData engineeringIndustrial dataSupply chainDigital manufacturingCloud platforms
Education:
Skills:System thinkingStructured approachPragmatismCommunicationOwnership
Tech Stack:SQLPythonData modellingData pipelinesAPIsAWSAzureSiemensSAPPLCsSCADAMESERPCloud platforms

Company Brief

Reckitt
Global consumer goods company producing health, hygiene, and home products across well-known brands. Operates in multiple markets offering over-the-counter health, personal care, and household cleaning products to consumers worldwide.
Industry: FMCG
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Slough, United Kingdom
Founded: 1999
WebsiteLinkedIn