Professional, Data Analyst

At Cotality, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society. Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry. Job Description: Join the Cotality team working on cutting edge solutions for the industry, with next-gen technology such as cloud native applications, machine learning, artificial intelligence, augmented reality, drones, and more.  We are constantly developing innovative solutions that make the real estate ecosystem smarter, more connected and more efficient. As a Data Analyst – Data Engineering at Cotality, you’ll collaborate within a multi-disciplinary team of analysts, data engineers, data scientists and geospatial analytics. This role offers significant opportunities to learn, innovate, and create high-impact, market-shaping data solutions. Job Responsibilities: · Design, build, and maintain data pipelines and ETL workflows using GCP services (e.g., BigQuery, Cloud Storage, Dataflow) and Airflow DAGs. Independently execute complex data engineering and analytic tasks according to established timelines, ensuring reliable and timely delivery of data products and reports. Write, optimize, and maintain complex SQL queries for data extraction, transformation, validation, and performance-tuned analytics. Maintain high-quality documentation for data pipelines, data models, and operational processes. Support internal and external users by analyzing datasets, debugging issues in pipelines, examining logs, and providing accurate, timely responses. Identify, troubleshoot, and resolve production issues related to data pipelines, data quality, and cloud workflows. Perform in-depth data analysis to support operational needs, client inquiries, and project initiatives Create structured datasets, dashboards, or analytical output that conveys trends and insights to business partners and leadership. Recommend and contribute to improvements in data engineering processes, coding standards, monitoring, and automation best practices. Collaborate across teams to support data-driven model performance monitoring and analytics. Provide technical guidance and cross-training to team members when needed. Job Qualifications: · Bachelor’s degree required; concentration in Computer Science, Engineering, Mathematics, Statistics, Data Science, or related field preferred. 3 years of hands-on experience in data analysis, data engineering, or pipeline development. Strong proficiency in SQL, including experience writing complex queries, optimizing performance, and working with large-scale datasets. Experience building and maintaining Airflow DAGs or similar workflow orchestration tools. Experience working in at least one major cloud environment (GCP preferred; AWS or Azure acceptable). Hands-on experience with GCP data services (BigQuery, Dataflow, Cloud Composer, Cloud Storage) is highly preferred. Proficiency in Python for scripting ETL tasks, data transformations, and automation. Experience with DevOps practices, including CI/CD pipelines. Strong understanding of data modeling, data quality validation, and debugging produ ... (truncated, view full listing at source)