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Rockwell Automation

Industrial automation hardware, software, services

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Strong experience in data engineering, data architecture, and enterprise analytics environments.
  • Advanced knowledge of SQL and relational database design.
  • Experience building and maintaining extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines.
  • Experience with Azure Data Platform technologies, including Azure Data Factory, Azure Synapse, Azure Databricks, Microsoft Fabric, Dataverse, and Azure SQL.
  • Experience supporting Power BI, tabular models, and semantic data layers.
  • Understanding of API integrations, enterprise applications, and data interoperability patterns.
  • Familiarity with modern DevOps practices, version control, and automated deployment methods.
  • Experience supporting service, manufacturing, industrial automation, engineering, or technology organizations.
  • Familiarity with ERP, CRM, service management, and financial systems.
  • Experience with AI, advanced analytics, or automation platforms.
  • Knowledge of Agile delivery methodologies and product-based delivery models.
  • Strategic thinking to understand business priorities and design scalable data solutions that support long-term organizational goals.
  • Collaboration and influence to build relationships across business, IT, and leadership teams and influence decisions without direct authority.
  • Problem-solving ability to identify root causes and implement sustainable solutions.

Responsibilities

  • Design, develop, and maintain scalable data pipelines integrating information from ERP, CRM, service management, financial, operational, and other enterprise systems.
  • Build and optimize data models, data warehouses, data marts, and semantic layers that support reporting and analytics requirements.
  • Develop and maintain ETL and ELT processes to ensure reliable and efficient data movement across platforms.
  • Support cloud-based and enterprise data architectures, focusing on scalability, performance, and maintainability.
  • Partner with enterprise IT teams to align LCS data solutions with corporate standards and technology roadmaps.
  • Provide trusted datasets for Power BI dashboards, operational reports, and self-service analytics.
  • Collaborate with BI developers and analysts to understand reporting requirements and translate them into data solutions.
  • Improve data availability, refresh performance, and reliability across business intelligence platforms.
  • Support development of KPI definitions and standardized business metrics.
  • Establish and maintain processes to improve data quality, consistency, integrity, and completeness.
  • Partner with business and functional leaders to define data standards, ownership, and governance procedures.
  • Implement monitoring, validation, and automated quality controls to ensure trusted business insights.
  • Support compliance with enterprise data management, privacy, cybersecurity, and governance requirements.
  • Develop data structures that support predictive analytics, automation, and AI-enabled solutions.
  • Collaborate with IT, automation, and AI teams to ensure data readiness for emerging technologies.
  • Support creation of reusable, governed data assets for future Copilot, AI, and advanced analytics initiatives.
  • Drive continuous improvement of analytics infrastructure and data engineering practices.
  • Act as a technical advisor on data architecture, integration approaches, and analytics enablement opportunities.
  • Translate complex technical concepts into clear business language for non-technical audiences.
  • Contribute to strategic initiatives that increase productivity, operational visibility, and business performance.
  • Deliver trusted, scalable data assets that support LCS reporting and analytics.
  • Improve data quality, consistency, and governance across critical business processes.
  • Increase adoption and effectiveness of BI and self-service analytics solutions.
  • Enable AI-ready and future-focused data foundations.
  • Reduce manual reporting effort through automation and modern data engineering practices.

Desired Qualifications

  • A Bachelor's or Associate degree in Information Technology, Computer Science, or Business Administration, or a related field, completed or in the final stages of completion, or equivalent professional experience.

About the Company

Rockwell Automation

Industrial automation hardware, software, services

Rockwell Automation provides hardware, software, and services to improve operational efficiency, reliability, and sustainability in industrial settings. It integrates automation components—sensors, controllers, software, and cloud/on‑premises platforms—to monitor, control, and optimize processes. It differentiates itself with a broad global portfolio, a strong emphasis on OT cybersecurity, maintenance management, digital twin capabilities, and industry‑specific sustainability solutions. Its goal is to help customers increase productivity, reduce operating costs, and meet environmental and reliability standards through integrated technology and ongoing support.

Company size
10,001+
Company stage
IPO
Headquarters
Milwaukee, WI
Founded
1903

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