HiringCafe
Posted 17h ago

DATA ENGINEER

@ Lindsay Precast
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Chicago, Illinois, United States
$78k-$128k/yrOnsiteFull Time
Responsibilities:Design pipelines, Develop integrations, Build data models
Requirements Summary:Bachelor's degree in Computer Science, Information Systems, Engineering, or related field; 3–5+ years data engineering; strong SQL; Python; experience with Microsoft 365 tools; relational databases; data warehousing; effective communication with non-technical stakeholders.
Technical Tools Mentioned:SQL, Python, Power Automate, Power BI, SharePoint, Microsoft 365, ERP
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Job Description

Position Summary

The Data Engineer is responsible for building and maintaining the data infrastructure that powers financial reporting, analytics, and operational decision-making across the Lindsay Family of Brands. This role supports the full lifecycle from data pipeline to finished report — designing reliable integrations, transforming raw data into clean, structured models, and delivering operational dashboards and reports that give leadership and teams across Lindsay Precast, Lindsay Renewables, and Dutchland the visibility they need to run the business.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines that move and transform data across ERP, operational, and reporting systems
  • Develop and maintain integrations between key platforms (ERP, Power BI, SharePoint, Microsoft 365, and third-party tools)
  • Partner with finance and operations stakeholders to understand reporting needs and translate them into durable data solutions
  • Build and maintain data models and semantic layers that support self-service analytics and Power BI reporting
  • Design, develop, and maintain operational reports and dashboards that surface key metrics for finance and operations leadership across all divisions
  • Automate repetitive data workflows using Power Automate, Python, or similar tools to reduce manual effort across the business
  • Support the evaluation and implementation of new data tools and platforms as the team’s data infrastructure evolves
  • Collaborate with the Business Systems Analysts to align data architecture with ERP workflows and business processes
  • Monitor pipeline health and proactively address failures, latency issues, or data anomalies before they impact the business

Success Metrics

  • Reliability and freshness of data pipelines feeding operational and financial reports
  • Reduction in manual data handling and spreadsheet-based workarounds across divisions
  • Data quality and consistency across key reporting areas (financials, production, inventory)
  • Stakeholder satisfaction with operational reports, dashboards, and self-service reporting capabilities