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Engineering Business Analyst

Job in Ripon, Fond du Lac County, Wisconsin, 54971, USA
Listing for: Alliance Laundry Systems LLC
Full Time position
Listed on 2026-05-19
Job specializations:
  • Engineering
    Data Science Manager
  • IT/Tech
    Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Overview

Alliance Laundry Systems is the world leader in commercial laundry equipment. Our Engineering organization spans three global sites - Ripon (WI), Pribor (Czech Republic), and Chonburi (Thailand) - and we are building the data and systems infrastructure needed to drive operational excellence  are looking for an Engineering Business Analyst  who can build a data andreportingecosystem from the ground up. This person will design and deliver dashboards that provide clear, actionable insights to Engineering leadership and cross-functional partners, while also deploying standardized systems and processes across all three global sites.

This is a high-impact, foundational role where we need someone who comes in ready to assess what exists, architect what’sneeded, and execute.

Responsibilities

Data Systems & Dashboard Development

  • Design, build, andmaintaina reporting and analytics framework for Engineering from the ground up defining metrics, data models, and visualization standards.
  • Develop and maintain

    Power BI dashboards that deliver clear, actionable insights and KPI trackers to Engineering leadership across operations, product development, product management, compliance, and project management.
  • Write and maintain

    SQL queries and data transformations to support reliable, governed data pipelines feeding engineering reports.
  • Participate in the company’s broader migration toward Sigma Computing and Snowflake, contributing engineering-specific reporting requirements and data models to the new platform.
  • Work across lines and partner with, and align systems with, other teams such as digital and finance.
  • Proactivelyidentifyopportunities to improve data quality, streamline existing reports, and reduce manual analytical work across the Engineering organization.
  • Leverage AI tools, including Claude / Anthropic AI, to accelerate analysis, automate insight generation, and explore new approaches to data storytelling.

Engineering Process & Systems Optimization

  • Analyze engineering workflows end-to-end toidentifyopportunities for efficiency, standardization, and automation across all three sites.
  • Build/maintain engineering processes including resource management, capacity tracking, and project pipeline visibility.
  • Develop working knowledge of core engineering systems (, SharePoint, and other platforms) and serve as a go-to resource for end users.
  • Support evaluation and implementation of new tools and platforms in partnership with IT and Engineering leadership.
  • Document system configurations, processes, and user guides to ensure sustainability and scalability.

Global Deployment & Collaboration

  • Deploy standardized dashboards, reporting processes, and system configurations to international Engineering teams in Pribor(Czech Republic) and Chonburi (Thailand).
  • Coordinate with cross-functional and cross-regional teams to ensure consistent data definitions, workflows, and tooling across all sites.
  • Adapt solutions for regional needs whilemaintainingglobal reporting standards and data integrity.
  • Supportchangemanagement anddeveloptraining materials to driveadoptionof new systems and processes at each site.
  • Build strong stakeholder relationships across geographies and time zones,demonstrating cultural awareness and communication adaptability.

Business Partnership & Stakeholder Engagement

  • Partner with Engineering leaders to deeply understand operational needs and translate them into well-structured, sustainable analytical and system solutions.
  • Prepare and deliver solution proposals, including scope, timeline, and expected business impact.
  • Communicate system and process changes clearly toimpactedengineering teams, ensuring alignment and adoption.
  • Collaborate with Data Engineers and IT to ensure engineering datasets are accurate, performant, and well-documented.
Qualifications

Education & Experience
:

  • Bachelor’s degree in Business, Engineering, Data Science, Information Systems, ora relatedfieldrequired.
  • 3+ years of experience in business analysis, data analytics, BI development, or engineering operations—withdemonstratedownership of building reporting solutions or systems from scratch.
  • Proven track recordof working across multiple sites, regions, or business…
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