Principal, Software Development Engineering

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 Principal Data Engineer / Data Architect with deep experience designing data models and building scalable batch and streaming data pipelines.

This individual will serve as a lead, or anchor, engineer responsible for designing and delivering reusable, enterprise-grade data capabilities used across Cotality. The role requires hands-on expertise with Google Cloud Platform, including Big Query and Dataflow, along with strong Python skills and experience working with graph technologies such as Neo4j or Google Spanner.

Experience with orchestration tools such as Apache Airflow is also important.

Key Responsibilities Design scalable data models and processing frameworks that support batch, streaming, API, analytics, and enterprise data use cases.

Establish data architecture standards and support broader data governance and information strategy.

Develop conceptual, logical, and physical data models that define how data is stored, processed, accessed, and integrated.

Define and document solution architecture, technical designs, requirements, and implementation approaches.

Lead an assigned engineering workstream while collaborating with other principal engineers on architecture, design, and technology best practices.

Provide technical leadership and guidance to engineering and support teams.

Help resolve complex data architecture and production issues across enterprise systems.

Support enterprise technology initiatives involving data warehouses, data lakes, data marts, and data mesh architectures.

Job Qualifications:

Bachelor’s degree in computer science, Engineering, or a related discipline, or equivalent professional experience.

Strong experience designing enterprise data architecture, data models, and scalable data-processing solutions.

Hands-on experience with Google Cloud Platform, particularly Big Query and Dataflow.

Strong programming experience with Python and PySpark.

Experience with SQL and No

SQL technologies, including the full lifecycle of database, data warehouse, and data mart design.

Experience working with graph databases or graph-oriented data solutions, such as Neo4j or Google Spanner.

Experience with distributed data-processing and orchestration technologies such as Apache Beam and Apache Airflow.

Demonstrated ability to develop clear architecture documentation, technical designs, standards, and specifications.

Preferred Experience

Experience with both Google Cloud Platform and AWS.Experience designing or supporting batch and streaming data pipelines.

Knowledge of enterprise data governance, architecture standards, and technology strategy.

Experience with modern data architecture concepts, including data lakes and data…