FPA Operations Analyst, NA

DWYER INSTRUMENTS, LLCMichigan City, IN

About The Position

The DwyerOmega FPA Operations Analyst North America reports to the Manager, Operations FPA. This position will support manufacturing teams in North America in driving cost efficiency & operational performance. This role plays a critical part in cost visibility, forecasting and operational analytics, partnering closely with manufacturing teams to translate manufacturing activity into actionable financial insights.

Requirements

  • 3+ years of experience in FP&A, operations finance, or cost accounting
  • Background in a manufacturing environment
  • Advanced Excel skills; experience with ERP systems
  • Familiarity with standard costing, COGS & COGM processes
  • Strong analytical & problem-solving skills
  • Ability to translate data into actionable insights
  • Effective communication & business partnering skills
  • High attention to detail & data integrity
  • Proactive, continuous improvement mindset
  • Motivated with a desire to learn

Responsibilities

  • Support COGS budget & forecast review, identifying risks and opportunities
  • Assist in COGM budget & forecast management, ensuring alignment with production plans and cost drivers
  • Perform COGM reporting & analysis, linking manufacturing activity to financial outcomes
  • Conduct operations variance analysis for product line reporting (volume, mix, labor, overhead)
  • Support cost & margin management through detailed analysis & reporting
  • Develop new reporting & analytics to improve visibility into manufacturing & performance
  • Improve visibility into manufacturing performance through standardized and scalable reporting
  • Support productivity & cost transformation initiatives, tracking performance & savings
  • Assist in identifying opportunities to improve efficiency & reduce costs
  • Manage the finance component of shop floor data collection, ensuring accuracy & alignment with financial reporting
  • Ensure integrity & consistency of operational & financial data across systems
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