Senior Data Engineer - CMD/CML

Rockwell Automation•Milwaukee, WI

7d•Hybrid

About The Position

As a Data Engineer –Enterprise Common Data Model/Common Data Layer, you will design, develop, and deliver scalable data management solutions that power Rockwell Automation's Enterprise. You will report to the Technical Leader for our Common Data Model / Common Data Layer team. You will collaborate with technical leads, analysts, architects, and product owners to shape the future of data-driven innovation across the enterprise.

Requirements

Bachelor's Degree or equivalent years of relevant work experience.

Nice To Haves

Typically requires 8+ years of relevant experience in data of software engineering.
Experience in the full systems development lifecycle and Agile methodologies.
Proficiency in data management technologies such as Azure ADF, ADLS, SQL, Databricks, SAP Data Services, and tabular models.
Strong understanding of server-side architectures, containerization, and DevOps practices.
Ability to manage multiple projects simultaneously and adapt quickly to new technologies and business needs.
Familiarity with open-source data management tools and domain-specific programming languages.
Experience working with business stakeholders to translate data into actionable insights.
Experience distilling complex data into clear narratives and recommendations.
Exposure to enterprise architecture and cross-functional collaboration in a global environment.

Responsibilities

Design, code, and test new data management solutions, including data acquisition, integration, and transformation pipelines using Microsoft Azure PaaS tools and DevOps methodologies.
Architect data structures and pipelines to enable "Data as a Service" across business units, ensuring scalability, reliability, and performance.
Develop and test infrastructure components in cloud and edge environments, leveraging tools like Azure ADF, ADLS, Databricks, and SAP Data Services.
Manage DevOps pipelines for continuous integration and deployment, and implement containerization models to support scalable deployments.
Collaborate with analysts, product owners, and business stakeholders to define requirements, write high-quality code, and support application enhancements.