Cloud Data Engineer

Job Description Summary

The Cloud Data Engineer supports the design, implementation, and maintenance of data pipelines, and predictive analytics workflows within Bentley’s cloud data ecosystem.

This role plays a key part in sourcing, transforming, and delivering data from enterprise systems to data lakes and warehouses while supporting analytics and future data science initiatives through scalable and secure infrastructure. The position involves collaboration with a variety of stakeholders including data analysts, and IT teams to ensure data is accessible, reliable, and actionable.

Essential Duties:

• Participate in Bentley’s data modernization efforts by developing cloud-based data pipelines and analytics infrastructure that support data engineering, analytics and predictive modeling needs.

• Build and maintain ETL/ELT processes to extract, transform, and load data from enterprise systems into cloud-based platforms such as Azure Synapse, Microsoft Fabric, and data lakes.

• Collaborate with data power users to design and implement infrastructure that supports analytics and machine learning workflows, including feature engineering pipelines and model outputs integration.

• Use Python or R to support data preparation, transformation, and integration tasks, and assist in developing reusable scripts and tools for analytics teams.

• Assist in the deployment and scaling of predictive models within Bentley’s cloud environment to support initiatives such as student success analytics.

• Partner with business users to clarify data and reporting requirements and ensure data pipelines meet evolving analytical needs.

• Design and support data warehouse structures (e.g., star schemas, fact and dimension tables) in alignment with reporting and ML readiness.

• Monitor and troubleshoot data jobs and model pipelines to ensure quality, integrity, and timely delivery of data.

• Implement logging, alerting, and monitoring processes to support data reliability and performance.

• Contribute to the development and maintenance of metadata management tools, including data catalogs and dictionaries, in collaboration with the data governance team.

• Support secure data access practices and collaborate with cloud engineering, integration, and security teams on compliance and infrastructure needs.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.

• Minimum of two consecutive years of post-graduate professional experience in data engineering or a related field is required, ideally with exposure to data science and machine learning infrastructure. Please note that internships do not count toward the required two years of experience.

• Minimum of 2 years of experience with the Azure data ecosystem, including tools such as Azure Synapse, Microsoft Fabric, and Azure Data Factory.

• Experience with Snaplogic for data integration and pipeline development.

• Proficiency in writing and optimizing SQL queries.

• Hands-on experience with Python or R for data wrangling, transformation, and basic ML tasks.

• Exposure to ML operations workflows and tools.

• Understanding of data modeling, ETL/ELT pipelines, and structured/semi-structured data processing.

• Ability to collaborate with cross-functional teams including data analysts, data scientists, and IT professionals.
   

Preferred Qualifications:

• Experience supporting predictive analytics initiatives (e.g., churn models, student success models, forecasting).

• Familiarity with visualization tools such as Power BI or similar.

• Exposure to metadata management and data governance practices.

• Experience in higher education or a similar mission-driven environment.

• Understanding of Workday data structures, particularly Workday Learning or Student, is a plus.

Work Environment:

• Typical office setting with extended screen time and computer use.

• Some campus travel may be required for meetings and collaboration.

• This role offers a flexible work arrangement, combining in-person attendance with remote work. On-site presence is required based on business needs, team collaboration, or scheduled meetings. This work arrangement is subject to change.

Bentley University requires references checks and may conduct other pre-employment screening.

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