Cloud Data Engineer

General Purpose & Essential Duties:

The Cloud Data Engineer designs, builds, and maintains scalable data pipelines and cloud-based data solutions that enable the organization to access, analyze, and utilize data effectively. This role supports Guardian Alarm’s evolving data strategy by integrating data from multiple systems, improving data accessibility, and enabling business intelligence and analytics initiatives. Working within the Azure ecosystem, the Cloud Data Engineer develops and maintains modern data pipelines, supports the organization’s data platform architecture, and collaborates with technical and business stakeholders to ensure reliable and high-quality data is available to support reporting, analytics, and operational decision-making.

Data Engineering & Platform Development

• Design, develop, and maintain scalable cloud-based data pipelines and data integration solutions within the Azure ecosystem.


• Build and operationalize data ingestion and transformation pipelines using tools such as Azure Data Factory, Python, and SQL.


• Support development and implementation of the organization’s cloud data platform, including Azure, Fabric and modern data architecture frameworks such as medallion architecture.


• Monitor and optimize data pipeline performance to ensure reliable and efficient data processing.

Data Integration & Pipeline Management

• Integrate data from multiple internal and external systems to support analytics, reporting, and operational data needs.


• Implement data transformations, data validation processes, and data quality controls to ensure reliable datasets.


• Analyze new data sources to determine usability, structure, and potential business value.


• Troubleshoot and resolve data pipeline failures, data inconsistencies, and system integration issues.

Data Governance, Security & Quality

• Support implementation of data governance practices, including data quality standards, data security, and proper data management processes.


• Assist in establishing best practices for data modeling, metadata management, and data lifecycle management.


• Ensure data solutions comply with organizational security and data protection standards.

Analytics & Reporting Support

• Collaborate with analytics, reporting, and business teams to ensure datasets support business intelligence and reporting requirements.


• Support the development and optimization of data models used in reporting tools such as Power BI.


• Assist stakeholders in understanding available data assets and how to leverage them effectively.

Collaboration & Technical Support

• Partner with IT teams, business stakeholders, and data users to deliver data solutions that support organizational objectives.


• Document data pipelines, architecture components, and technical processes to support long-term maintainability.


• Provide technical guidance to internal teams regarding the use and availability of data resources.

Required Skills, Abilities, Education & Experience

• Strong analytical and problem-solving skills with the ability to translate complex data challenges into practical solutions.


• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.


• Strong collaboration skills with the ability to work cross-functionally with IT and business teams.


• Experience working with cloud-based data platforms and modern data engineering tools.


• Strong SQL and data transformation skills.


• 4-6 years’ experience with Python or other scripting languages used for data processing and automation.


• 4-6 years’ experience with Azure data services such as Azure Data Factory, Fabric, or related tools preferred.


• Ability to manage multiple projects and priorities in a dynamic environment.


• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related STEM field, or equivalent practical experience.


• 4–6 years of experience in data engineering, data integration, or related data platform development roles.


• Experience working with cloud-based data platforms, preferably Microsoft Azure.


• 4-6 years experience building and maintaining data pipelines and data transformation processes.


• Experience supporting business intelligence and analytics environments preferred.