Senior Data Engineer - Zonda - Toronto, ON Job Description Senior Data Engineer: Senior Data Engineer – Zonda – Toronto, ON Company Overview CoStar Group (NASDAQ: CSGP) is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P; 500 Index, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives.

We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers. We’ve continually refined, transformed, and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate.

About Zonda Zonda is redefining the future of housing. We are perfectly placed in the heart of the fast-growing real estate industry. We are making big bets on the future of real-estate, trailblazing a 2030 vision for the industry. Here at Zonda, you’ll be able to use your passion and curiosity to drive the next generation of real estate analysts, advisors, technologists, and marketers.

Learn more about Zonda

The Senior Data Engineer is responsible for designing, building, and operating reliable, scalable data pipelines and data products across a modern cloud data platform.





This is a hands‑on engineering role focused on data pipeline development, performance optimization, production reliability, and continuous improvement. The Senior Data Engineer will independently own complex data engineering work from requirements through production and ensure solutions are maintainable, testable, observable, and performant.

Responsibilities

Design, build, test, and maintain reliable, scalable data pipelines and data products.

Develop and optimize data transformations and orchestrations using SQL, Python, dbt, Airflow, Glue, PostgreSQL, and Snowflake.

Translate business requirements into maintainable technical designs and production‑ready solutions.

Implement automated testing, data‑quality checks, monitoring, failure handling, and recovery.

Optimize large‑scale data workloads for performance, scalability, and cost.

Troubleshoot production issues and perform root‑cause analysis across pipelines and databases.

Follow Git‑based development, code review, CI/CD, and controlled release practices.

Ensure data products are documented, observable, governed, and supported by appropriate metadata and lineage.

Reduce technical debt, manual processes, and recurring operational issues through automation and improved design.

Collaborate with Product Management, Application Engineering and business stakeholders.





Basic Qualifications

6+ years of professional experience in data engineering or a closely related discipline.

Solid Python development skills for data pipelines, automation, integrations, and supporting data applications.

Advanced SQL skills and experience working with large‑scale datasets.

Strong understanding of data modeling, database design, and data transformation patterns.

Experience with dbt, including model development, dependency management, testing, incremental processing, and production deployment.

Experience with Airflow, including DAG development, orchestration, dependencies, retries, failure handling, scheduling, and production operations.

Hands‑on PostgreSQL experience, including complex SQL development, database design, indexing, query optimization, and performance tuning.

Hands‑on Snowflake experience in production data workloads context.

Experience working with AWS data services such as S3, RDS/Aurora, Glue, MWAA, IAM, and CloudWatch.

Experience implementing automated data validation and quality controls.

Experience with Git, pull requests, code review, conflict resolution and CI/CD workflows.

Demonstrated ability to troubleshoot complex production pipeline and data issues.

Understanding of monitoring, failure recovery, and production support practices.

Preferred Qualifications

Experience with Amazon Aurora PostgreSQL.

Experience working with datasets containing hundreds of millions or billions of records.

Experience with AWS Glue and Amazon MWAA.

Experience with geospatial data and PostGIS.

Experience with SQL Server.

Experience with DataH

📌 Senior Data Engineer (Toronto)
🏢 Costar Group
📍 Toronto