Cloud 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!

Job Description

Position Summary

The Cloud Engineer, focused on cloud data platforms and integration, is responsible for building, supporting, and maintaining scalable cloud-based data solutions across Azure and AWS. This role provides hands-on engineering support for Databricks, data transformation, API ingestion, and cloud-native services while following enterprise standards for security, reliability, governance, and cost efficiency. The Cloud Engineer partners with technical teams and business stakeholders to enable trusted data delivery for reporting, analytics, AI, and operational decision-making. This position reports directly to the FinOps Technical Leader and works closely with the FinOps team to support cloud and AI financial management, data engineering, automation, and reporting initiatives.

Key Responsibilities

• Build, support, and maintain cloud-based data solutions using Databricks, Azure, and AWS services.
• Develop data ingestion and transformation pipelines using Spark, PySpark, SQL, Python, and ETL/ELT patterns.
• Support API-based data ingestion from internal, vendor, cloud, and enterprise platforms.
• Assist with monitoring, troubleshooting, documentation, and operational support for cloud data pipelines and integrations.
• Collaborate with architecture, security, FinOps, analytics, and business teams to deliver reliable and cost-effective data solutions.
• Follow engineering standards, governance practices, and deployment processes for secure and scalable delivery.

Basic Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related field (or equivalent experience).
• 5+ years of experience in cloud engineering, data engineering, systems integration, or related technical roles.
• Hands-on experience with Databricks, Spark, SQL, Python, and data transformation or pipeline development.
• Experience developing or consuming REST APIs for data ingestion and enterprise system integration.
• Experience building or supporting cloud-native solutions within Microsoft Azure and Amazon Web Services (AWS).
• English proficiency required, with the ability to communicate clearly in written and spoken English with technical and business stakeholders.
• Proven ability to work effectively in a matrixed, cross-functional environment.

Preferred Qualifications:

• Experience with Azure services such as Azure Databricks, Azure Data Factory, Azure Storage, Azure Functions, Azure Key Vault, Azure Monitor, or related services.
• Experience with AWS services such as S3, Lambda, Glue, Athena, RDS, CloudWatch, or related services.
• Experience with Delta Lake, lakehouse architecture, data modeling, or data governance concepts.
• Familiarity with Azure DevOps, GitHub, Git, Terraform, Bicep, ARM templates, or CloudFormation.
• Experience supporting analytics platforms such as Power BI, Microsoft Fabric, Synapse, or similar reporting and data consumption platforms.
• Understanding of cloud security practices, identity and access management, encryption, secrets management, and compliance requirements.
• Databricks, Microsoft Azure, AWS, or data engineering certifications preferred.
• Strong critical thinking and problem-solving skills, with experience resolving data, integration, or platform issues.
• Self-directed and proactive, with strong ownership, accountability, communication, and documentation skills.

Rockwell Automation’s hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.