Data Engineer

Rockwell Automation is a global technology leader focused on helping the world’s manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better. We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that’s you we would love to have you join us!

Position Summary The LCS Data Engineer is responsible for designing, building, maintaining, and optimizing the data platforms, pipelines, and integration frameworks that power Business Intelligence, analytics, AI, and operational reporting across Lifecycle Services (LCS). Reporting into the LCS Business Intelligence & Data Governance Manager, this role serves as a critical bridge between business stakeholders, BI developers, analysts, IT, and digital teams, ensuring that LCS data is accurate, accessible, secure, scalable, and ready to support data-driven decision making.

Data Architecture & Engineering Design, develop, and maintain scalable data pipelines that integrate 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 ELT/ETL processes to ensure reliable and efficient movement of data across platforms. Support cloud-based and enterprise data architectures with a focus on scalability, performance, and maintainability. Partner with enterprise IT teams to align LCS data solutions with corporate standards and technology roadmaps. Business Intelligence Enablement Provide high-quality, 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 robust data solutions. Improve data availability, refresh performance, and reliability across key business intelligence platforms. Support development of KPI definitions and standardized business metrics. Data Quality & Governance 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. AI & Advanced Analytics Readiness 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 that enable future Copilot, AI, and advanced analytics initiatives. Drive continuous improvement of analytics infrastructure and data engineering practices. Stakeholder Partnership 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. The Essentials - You Will Have: Technical Expertise Strong experience in data engineering, data architecture, and enterprise analytics environments. Advanced knowledge of SQL and relational database design. Experience building and maintaining ETL/ELT pipelines. Experience with Azure Data Platform technologies such as: Azure Data Factory Azure