Top Senior Level Real Estate Data & Analytics Jobs

As the Manager of Business Intelligence, you'll lead a team to provide analytics and reporting, driving performance and insights across the organization, while managing relationships with stakeholders and enhancing data processes.

The role involves managing SitusAMC's Database Administration team, overseeing AWS RDS and EC2 databases, ensuring performance, security, and compliance with industry standards. Responsibilities include mentoring, optimizing database operations, collaborating on applications, and leading modernization efforts.

As a Sr. Staff Data Scientist, you'll lead key analytics projects, create dashboards, and link data-driven insights to business strategies, improving performance.

The Data Quality Engineer will design and implement data quality frameworks, manage tools for data profiling, enforce quality rules, and automate processes using AI in order to ensure data integrity across platforms.

Lead impactful business intelligence initiatives, own enterprise metrics, and oversee BI products to drive decision-making and improve customer experience.

As a Senior Data Analyst, you will leverage advanced data analytics to bridge executive vision with technical implementation, mentor team members, and develop data models to inform business decisions.

The Lead Data Analyst will oversee marketplace analytics, define operational metrics, clean data, conduct user behavior analysis, and partner with leadership to drive product strategy and revenue growth.

The VP of Portfolio Strategy & Analytics will lead data-driven insights into asset performance, ensuring strategic capital allocation and optimizing portfolio returns. They will collaborate with various departments to enhance decision-making, reporting, and analytics infrastructure.

The Senior Data Pipeline Engineer will manage and evolve Clever's data infrastructure, focusing on AWS, Airflow, Databricks, and ensuring reliable data ingestion and compliance.

Design, build, and operate secure, scalable cloud data pipelines, data lake/warehouse solutions, and governance. Integrate new sources, support analytics and BI, mentor junior engineers, enable data accessibility, and provide production support.