Cloud Data Engineer: SQL, ETL & Power Platform

CBRE; Washington (District of Columbia); On-site; USD 80,000 - 90,000; Full time

Job summary

CBRE in Washington, DC is seeking a Database Analyst to design, build, and optimize data pipelines and platforms supporting analytics and operations. You will work across cloud data platforms, ensure data quality, and develop interfaces for users to update data and maintain business processes.

The role emphasizes strong SQL, Azure SQL and Power Platform experience, collaboration with data analysts and engineers, and ownership from data ingestion to production deployment.

Qualifications

• Experience building production ETL/ELT pipelines for relational databases such as SQL Server or Azure SQL.
• Strong SQL with window functions, joins, CTEs, and data modeling.
• Experience with Python for data processing and API integration; Git version control.

Responsibilities

• Design, build, and improve data pipelines and platforms supporting analytics and operations.
• Collaborate with analysts, stakeholders, and engineers to translate data requirements.
• Develop solutions using Power Platform products including PowerApps and Power Automate.
• Ensure data quality, security, backups, and disaster recovery plans.
• Maintain documentation and assist end-users on database systems.

Skills

Advanced SQL

Python

Power Platform

Azure SQL

AWS

Git

Power BI

Microsoft Office

Data warehousing

ETL/ELT pipelines

Education

Bachelor's degree or equivalent

Tools

SQL Server

Azure

Power Apps

Power Automate

SharePoint Lists

Fabric

Job description

CBRE in Washington, DC is seeking a Database Analyst to design, build, and optimize data pipelines and platforms supporting analytics and operations. You will work across cloud data platforms, ensure data quality, and develop interfaces for users to update data and maintain business processes.

The role emphasizes strong SQL, Azure SQL and Power Platform experience, collaboration with data analysts and engineers, and ownership from data ingestion to production deployment.