Data Engineer

Hercules Industries • Denver, CO

1d • Onsite

About The Position

The Data Engineer at Hercules Industries is responsible for building, governing, and continuously improving the data foundation that powers decision-making across supply chain, operations, and commercial functions. This role serves as both a steward of data integrity and a builder of scalable data infrastructure, enabling accurate, connected, and actionable data across the organization. The Data Engineer directly supports advanced analytics, MRP optimization, and real-time decision-making, forming a critical component of Hercules’ transition to a modern, data-centric enterprise. The purpose of this role is to own the design, integrity, and performance of Hercules’ data ecosystem by establishing scalable architecture, governing data quality, and enabling accessible, reliable data that drives operational and strategic decision-making across the business.

Requirements

• Bachelor’s degree preferred (Data Engineering, Computer Science, Information Systems, or related field)
• Experience with data architecture, data pipelines, and system integration
• Experience working with ERP systems, data warehouses, and analytics platforms
• Strong understanding of data governance, data quality, and master data management
• Proficiency in data tools, SQL, and data modeling concepts
• Strong analytical and problem-solving skills
• Ability to translate business needs into technical solutions
• Ability to effectively communicate with customers and staff to make an accurate assessment of customer needs.
• Ability to perform basic mathematical calculations required to accurately complete assigned tasks.
• Intermediate/Advanced computer skills, including Microsoft Office and ability to learn any additional software needed to perform job duties.
• Ability to interpret a variety of instructions furnished in oral or written form.
• Ability to use sound judgment and problem-solving skills.

Nice To Haves

• Experience supporting supply chain, operations, or business analytics environments preferred
• Experience working cross-functionally in a fast-paced environment

Responsibilities

• Establish and enforce data governance standards across ERP, data warehouse, and connected systems
• Ensure accuracy, consistency, and reliability of core datasets (item master, lead times, safety stock, supplier and customer data)
• Identify and remediate data quality issues through structured audits and data initiatives
• Define ownership, workflows, and controls for maintaining high-quality master data
• Implement monitoring systems to proactively detect and resolve data anomalies
• Design and maintain scalable data architecture connecting ERP (Infor M3), data warehouse, CRM, and external systems
• Build and manage data pipelines (ETL/ELT) to ensure timely and accurate data availability
• Enable seamless data flow across systems to support real-time and near-real-time decisions
• Standardize data models to support analytics and operational processes
• Ensure MRP and planning systems are supported by accurate and structured data
• Partner with supply chain and operations to optimize lead times, safety stock, and planning parameters
• Identify and resolve data issues driving inefficiencies in purchasing, production, and inventory
• Support the evolution of MRP into a proactive, optimized planning system
• Build data models that make data accessible for analysts, data scientists, and business leaders
• Develop datasets that enable rapid analysis and insight generation
• Support dashboards, reporting tools, and self-service analytics capabilities
• Ensure key business metrics are consistently defined and trusted
• Partner with Data Science to provide clean, structured datasets for modeling
• Translate business requirements into data architecture solutions
• Work with supply chain, operations, and finance leaders to prioritize data needs
• Serve as a bridge between technical systems and business application
• Lead initiatives to modernize data infrastructure and capabilities
• Identify opportunities to automate manual processes and eliminate workarounds
• Drive transition toward a fully integrated, data-driven operating model
• Establish best practices for data engineering within the organization

Benefits

• Employee-owned (ESOP), aligning effort with long-term value creation

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level