Rockwell Automation Hiring Cloud Engineer in India | Hybrid

Job Overview

Rockwell Automation is hiring a Cloud Engineer for a full-time hybrid opportunity in India, with locations listed in New Delhi (Noida), Pune, Hyderabad, and Bangalore. The role focuses on cloud data platforms, enterprise integration, data pipelines, and cloud-native engineering across Microsoft Azure and Amazon Web Services. The engineer will help build and support reliable data solutions that serve reporting, analytics, AI, and operational decision-making needs.

The position combines hands-on engineering with operational support. The successful candidate will work with Databricks, Spark, PySpark, SQL, Python, REST APIs, ETL and ELT patterns, and cloud services. The role also works closely with architecture, security, FinOps, analytics, and business teams to deliver data solutions that are secure, governed, reliable, and cost-conscious.

Key Responsibilities

• Build, maintain, and support cloud-based data solutions using Databricks, Azure, AWS, and related services.
• Develop scalable data ingestion and transformation pipelines using Spark, PySpark, SQL, Python, and ETL or ELT approaches.
• Create or support API-based data ingestion from internal platforms, vendors, cloud services, and enterprise systems.
• Monitor cloud data pipelines and integrations and investigate operational issues when they occur.
• Troubleshoot data, integration, and platform problems while supporting reliable day-to-day operations.
• Maintain technical documentation and follow established deployment and engineering processes.
• Work with architecture and security teams to deliver solutions that meet enterprise standards.
• Collaborate with FinOps, analytics, and business stakeholders to support practical and cost-effective data delivery.
• Follow governance, security, reliability, and operational standards when developing and supporting cloud solutions.

Required Skills

Strong hands-on experience with Databricks, Spark, SQL, and Python is required. Candidates should understand how to design and maintain data transformation and pipeline solutions and should be comfortable working with structured data processing workflows.

Experience with REST APIs is important because the role includes integrating data from enterprise, vendor, internal, and cloud platforms. Applicants should understand API-based ingestion and the practical challenges involved in connecting multiple systems.

The position requires experience with both Microsoft Azure and Amazon Web Services cloud environments. Candidates should understand cloud-native solution development and be able to support data platforms and integrations in production-oriented environments.

A solid understanding of data engineering practices, monitoring, troubleshooting, documentation, and deployment processes will help candidates succeed. The role also requires the ability to work within enterprise standards covering security, governance, reliability, and cost efficiency.

Preferred Skills

Experience with Azure services such as Azure Databricks, Azure Data Factory, Azure Storage, Azure Functions, Azure Key Vault, and Azure Monitor is valuable. AWS experience involving services such as S3, Lambda, Glue, Athena, RDS, and CloudWatch is also preferred.

Additional experience with Delta Lake, lakehouse architecture, data modeling, and data governance can strengthen an application. Familiarity with Azure DevOps, GitHub, Git, Terraform, Bicep, ARM templates, or CloudFormation is also useful for cloud infrastructure and deployment work.

Candidates with exposure to analytics and data consumption platforms such as Power BI, Microsoft Fabric, or Synapse may also be well aligned. Knowledge of cloud security practices, identity and access management, encryption, secrets management, and compliance requirements is desirable.

Relevant certifications in Databricks, Microsoft Azure, AWS, or data engineering are preferred but are not stated as mandatory.

Education

A bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related field is required. Equivalent experience may also be considered according to the source job description.

Experience

A minimum of 5 years of experience in cloud engineering, data engineering, systems integration, or a related technical role is required. The source job description does not specify a maximum experience level, so no maximum has been inferred.

Required Technologies

The core technology stack includes Databricks, Spark, PySpark, SQL, Python, REST APIs, ETL, ELT, Microsoft Azure, and Amazon Web Services. Relevant Azure services include Azure Databricks, Azure Data Factory, Azure Storage, Azure Functions, Azure Key Vault, and Azure Monitor. Relevant AWS services include S3, Lambda, Glue, Athena, RDS, and CloudWatch.

Additional technologies and platforms mentioned include Delta Lake, lakehouse architecture, Power BI, Microsoft Fabric, Synapse, Azure DevOps, GitHub, Git, Terraform, Bicep, ARM templates, and CloudFormation.

Soft Skills

Clear communication is important because the Cloud Engineer works with technical and business stakeholders across a matrixed environment. English proficiency is required for written and spoken communication.

Strong critical thinking and problem-solving skills are valuable for resolving data, integration, and platform issues. The role also calls for ownership, accountability, proactive working habits, and good documentation skills. Candidates should be comfortable collaborating across architecture, security, FinOps, analytics, engineering, and business functions.

Benefits of Working in this Role

This role provides practical exposure to modern cloud data engineering across Azure and AWS. Professionals can develop deeper skills in Databricks, Spark, Python, SQL, cloud-native services, data integration, lakehouse architecture, and data governance.

The position also provides experience working at the intersection of cloud engineering, analytics, AI-related data needs, FinOps, security, and enterprise governance. This combination can help engineers broaden their understanding of how cloud data platforms are designed, operated, and optimized for business use.

Work Mode

This is a hybrid full-time position.

Location

The role is available at the listed Rockwell Automation locations in New Delhi (Noida), Pune, Hyderabad, and Bangalore, India. It is relevant to candidates searching for Rockwell Automation jobs, Cloud Engineer jobs, cloud jobs, data engineering jobs, Azure jobs, AWS jobs, Databricks jobs, Python jobs, SQL jobs, and IT jobs in these locations.

Who Should Apply

This opportunity is suitable for experienced cloud or data engineers with at least 5 years of relevant professional experience. Candidates should have strong hands-on skills in Databricks, Spark, SQL, Python, REST APIs, and cloud data platforms.

Applicants should be comfortable supporting cloud-based data pipelines, troubleshooting integrations, working with multiple technical teams, and following enterprise security and governance practices. Experience with Azure and AWS is particularly relevant, while knowledge of infrastructure automation, analytics platforms, data governance, and cloud security can further strengthen an application.

Career Growth

Working across cloud engineering, data platforms, Databricks, Azure, AWS, automation, integration, and FinOps-related initiatives can support career growth toward senior cloud engineering, data engineering, platform engineering, cloud architecture, or specialized cloud data roles. Continued development in infrastructure automation, security, governance, and lakehouse technologies can broaden future technical opportunities.

Application Advice

Tailor your resume to the core requirements of the role. Highlight hands-on experience with Databricks, Spark, PySpark, Python, SQL, REST APIs, Azure, and AWS. Describe the data pipelines or integrations you have built or supported and explain the business or operational value they delivered.

If you have worked with Azure Data Factory, Azure Functions, Azure Storage, Azure Key Vault, Azure Monitor, AWS S3, Lambda, Glue, Athena, RDS, or CloudWatch, list the relevant services clearly. Also mention experience with Delta Lake, lakehouse architecture, Terraform, Git, Azure DevOps, GitHub, Power BI, Microsoft Fabric, Synapse, or cloud security where applicable.

The listed application deadline is August 28, 2026. Review your technical experience carefully and apply through the employer's official application process before the stated deadline.