Principal, Data Engineer

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:

We are seeking a highly motivated and self-driven Data Engineer with a strong background in building scalable batch and streaming data pipelines. The ideal candidate brings deep expertise in Google Cloud Platform (GCP), with hands-on experience in Dataflow, BigQuery, Python, and graph databases such as Neo4j and Google Spanner. Familiarity with orchestration tools like Apache Airflow is essential.

In this role, you will serve as a lead (anchor) engineer, driving the design and delivery of reusable, enterprise-grade data capabilities leveraged across Cotality. You will play a key role in building robust, scalable, and efficient data processing frameworks that support a wide range of business applications and strategic initiatives.

Key Responsibilities

• Design and implement scalable, high-performance data solutions using industry best practices and modern technologies, ensuring optimal integration, reliability, scalability, flexibility, and maintainability
• Translate business requirements and processes into well-architected technical solutions, aligning with enterprise architecture standards and long-term technology strategy
• Define and document solution architecture, technical designs, and requirements to support business objectives while balancing practical implementation and strategic vision
• Provide technical leadership and guidance to engineering and support teams, ensuring alignment with business and IT strategies
• Develop and present architecture and design artifacts to both technical and non-technical stakeholders
• Proactively identify challenges, assess downstream impacts across business domains, and drive solution design through research, validation, and stakeholder consensus
• Apply industry and domain best practices, offering architectural guidance and strategic input to business and technology leadership
• Evaluate the impact of new solutions on existing architecture, ensuring compliance with enterprise standards and governance frameworks
• Contribute to enterprise-wide technology initiatives and support critical issue resolution when needed
• Actively participate in team ceremonies, provide status updates, and support overall project governance and execution

Job Qualifications:

Job Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related discipline (or equivalent work experience)
• 7+ years of experience in IT, with strong expertise in data architecture, integrating and analyzing disparate data sources, and driving data quality improvements-preferably within the mortgage, real estate, or insurance domains
• Deep understanding of data modeling techniques to support technology optimization, data consolidation, and strategic architecture planning
• Strong knowledge of the full lifecycle of database, data warehouse, and data mart design and development
• Proven experience in enterprise data architecture, including governance, standards, and strategy development
• Demonstrated ability to resolve complex enterprise-wide data architecture challenges
• Expertise in designing data management solutions aligned with strategic technology roadmaps and emerging industry trends
• Proficiency with data modeling tools and strong experience across SQL and NoSQL technologies

Technical Skills & Experience

• Hands-on experience with cloud platforms such as AWS and Google Cloud Platform (GCP)
• Strong programming skills in Python and PySpark
• Experience with AI development frameworks and lifecycle methodologies (e.g., BMAD, Spec Kit)
• Experience with big data and distributed processing technologies such as Hadoop, Spark, and