Maschmeyer Concrete

Maschmeyer Concrete

Data Analyst

Lake Park, FL

Sponsorship not specifiedDetected 31 days ago
PythonSQLSnowflakeRedshiftdbtData AnalysisData VisualizationStatisticsA/B TestingFinancial ModelingForecastingBudgetingExcelLeadershipCommunicationProblem Solving

About the role

  • We are looking for a sharp, curious, and driven Analyst to join our team.
  • Whether your background leans quantitative, financial, or operational, we want someone who is energized by solving problems and communicating findings with impact.

Responsibilities

  • Build and maintain dashboards, reports, and visualizations that give stakeholders real-time visibility into key metrics
  • Support financial planning, forecasting, and budgeting cycles with accurate, well-documented models
  • Partner with business units to understand goals, translate them into analytical frameworks, and deliver actionable recommendations

Requirements

  • Bachelor's degree in Finance, Economics, Statistics, Mathematics, Computer Science, or a related field
  • 2-5 years of experience in a data, finance, or business analysis role
  • Proficiency in SQL for querying and manipulating data
  • Experience with at least one BI or visualization tool (Tableau, Power BI, Looker, or similar)
  • Solid analytical thinking with the ability to break down ambiguous problems
  • Excellent written and verbal communication skills - you can tell a clear story with data
  • Experience with Python or R for data analysis and automation
  • Familiarity with financial statements (P&L, balance sheet, cash flow)
  • Experience in a fast-paced, high-growth, or cross-functional environment

Compensation

  • Competitive salary commensurate with experience

Benefits

  • Comprehensive health, dental, and vision benefits
  • Flexible work arrangements and generous PTO
  • Professional development budget and support for continued learning

Company info

  • What We're Looking For

This listing is sourced directly from Maschmeyer Concrete's careers page and normalized into a canonical job model.