Data Specialist

Allied Reliability; Lake Norden (SD); On-site; USD 60,000 - 80,000; Full time

Job summary

Allied Reliability is seeking an Asset Hierarchy Validation & Attribute Data Specialist to support a Lake Norden, SD facility Reliability Improvement Journey by validating existing equipment hierarchy within Maximo CMMS and collecting detailed asset attribute data down to the replaceable component level.

The role entails shop floor walkdowns, capturing nameplate data, maintaining data governance, and collaborating with Maintenance, Reliability, Operations teams and Allied Reliability personnel.

Qualifications

• Minimum 3–5 years of industrial maintenance, reliability, CMMS, or asset management experience.
• Experience in manufacturing environments preferred.
• Familiarity with asset hierarchy concepts and data governance.

Responsibilities

• Validate existing Maximo asset hierarchy against field conditions.
• Confirm assets are identified to the appropriate maintenance/replaceable components.
• Identify missing, duplicate, or misstructured assets and verify parent/child relationships.
• Perform shop floor walkdowns to collect equipment attribute data and photographs.
• Transfer data into CMMS/EAM and support data standardization.

Skills

Industrial maintenance

CMMS/EAM familiarity

Data collection

Field walkdowns

Documentation

Tools

Maximo CMMS

AI-assisted tools

Job description

*This is not an IT or AI based position*- We are seeking Maintenance and Reliability Manufacturing personnel. *Local candidates only*

Allied Reliability is seeking an Asset Hierarchy Validation & Attribute Data Specialist (Long-Term Project Assignment) to support a Lake Norden, SD facility Reliability Improvement Journey (RIJ) by validating existing equipment hierarchy within Maximo CMMS and collecting detailed asset attribute data down to the replaceable component level.

• This role is critical to enabling:Equipment Maintenance Plan (EMP) development
• Accurate spare parts identification
• Improved maintenance execution efficiency
• Long-term asset data governance and sustainment

The individual will perform shop floor equipment walkdowns utilizing Allied Reliability’s digital walkdown tools to capture equipment nameplate data, photographs, asset attributes, component relationships, and maintainability information.

The role will work under the guidance of an Allied Reliability Senior Supervisor during onboarding and transition into a semi-independent execution role with periodic oversight and auditing.

Primary Responsibilities

• Asset Hierarchy ValidationValidate existing Maximo asset hierarchy against physical field conditions
• Confirm assets are identified to the appropriate maintainable and replaceable component level
• Identify missing, duplicate, incorrectly assigned, or improperly structured assets
• Validate parent/child equipment relationships

Attribute Data Collection

• Collect and validate critical equipment attribute data including:Motor HP
• Voltage
• Amperage
• RPM
• Frame size
• Manufacturer
• Serial number
• Bearing information
• Critical spare information
• Additional maintainability-related data as required
• Digital Walkdown ExecutionUtilize Allied Reliability walkdown tools in the field
• Capture and organize equipment photographs and nameplate data
• Use AI-assisted identification tools where nameplate information is damaged or unavailable
• Perform manual verification when automated identification is insufficient
• Maintain organized and traceable field records
• Data Governance & QualityTransfer collected data into SmartCBM staging environment
• Assist with formatting and standardization of asset data
• Support validation prior to loading into Maximo test and production environments
• Maintain data integrity and naming consistency
• Identify gaps impacting EMP development and maintenance execution
• CollaborationWork closely with Maintenance, Reliability, Operations, and Allied Reliability personnel
• Participate in periodic audits and review sessions with Allied supervisory personnel
• Support long-term sustainment of hierarchy and asset data governance practices

Required Qualifications

• Technical Background Minimum 3–5 years of industrial maintenance, reliability, CMMS, or asset management experience
• Experience within manufacturing, food & beverage, industrial processing, or heavy industry environments preferred
• Working knowledge of rotating equipment and industrial assets including:
• Motors
• Pumps
• Gearboxes
• Valves
• Process equipment
• Instrumentation
• CMMS ExperienceExperience working within a CMMS/EAM platform required
• Understanding of:
• Asset hierarchy structures
• Equipment parent/child relationships
• Functional locations
• Asset records
• Equipment classifications
• Spare parts relationships
• Data & Documentation SkillsStrong attention to detail
• Ability to maintain structured and consistent data
• Comfortable working with spreadsheets, digital tools, and mobile applications
• Ability to identify inconsistencies and missing information
• Field Execution CapabilityComfortable working in active manufacturing environments
• Ability to perform extensive shop floor walkdowns
• Ability to read nameplates, drawings, and basic technical documentation
• Ability to work independently after onboarding
• Preferred QualificationsExperience supporting Reliability Improvement initiatives
• Exposure to Equipment Maintenance Plans (EMP), PM optimization, or RCM methodologies
• Experience with SmartCBM, APM, or digital asset management tools
• Understanding of ISO 14224 asset taxonomy concepts
• Familiarity with dairy, food processing, or continuous process manufacturing environments
• Experience validating or building hierarchy to maintainable component level
• Ideal Candidate ProfileMechanically inclined
• Detail-oriented
• Organized
• Comfortable on the shop floor
• Technically curious
• Capable of balancing field execution with data accuracy
• Able to recognize the difference between operational equipment grouping and maintainable component structure

This role is best suited for someone with practical maintenance or reliability experience rather than a purely administrative data-entry background.