Senior Data Platform Engineer - Zonda - Toronto, Ontario

Senior Data Platform Engineer - Zonda - Toronto, Ontario
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Job Description
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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
We are looking for a Senior Data Platform Engineer to design, automate, and operate the shared capabilities that underpin our enterprise data platform.
Our environment includes Snowflake, AWS Aurora PostgreSQL, Amazon MWAA/Apache Airflow, dbt, AWS Glue, Amazon S3, Amazon EKS, DataHub, Grafana, CloudWatch, and GitHub.
This is a hands-on senior engineering role at the intersection of data engineering, Data DevOps, cloud platform engineering, and production reliability.
The role is not primarily focused on building individual business pipelines or administering enterprise cloud infrastructure. It owns Data Platform infrastructure and automation within the data domain while partnering with enterprise Infrastructure and Security teams on underlying cloud, networking, identity, and security services. Its purpose is to build the shared frameworks, automation, and operational capabilities that allow Data Engineers to deliver data products safely, consistently, and efficiently. The role does not own database-engine administration, query tuning, indexing, vacuum management, database capacity planning, or database-level performance troubleshooting. These responsibilities sit with Database Administration, with Data Platform Engineering providing the automation, deployment, and infrastructure capabilities around the database platforms.
You will own major platform capabilities end to end — from architecture and automation through production operation, reliability, and continuous improvement.
This position will be located in Toronto, Ontario and is in office Monday through Friday.
Responsibilities:
Data Platform & Data DevOps
Own the Data DevOps framework, standards and automation across Snowflake and AWS RDS/Aurora database platforms.
Establish source-controlled schema versioning, database migration workflows, environment promotion, deployment validation, and deployment rollback practices.
Implement Snowflake CI/CD and database deployment using schemachange or equivalent tooling.
Implement automated schema migration and versioning for AWS RDS/Aurora databases using Flyway or equivalent tooling.
Automate Snowflake roles, grants, policies, and supported configuration through Infrastructure as Code.
Reduce routine direct production changes through repeatable, auditable deployment workflows.
dbt, Airflow & Data Delivery
Establish platform standards for dbt and Apache Airflow / Amazon MWAA.
Build and maintain reusable CI/CD patterns for transformations, pipelines, dependencies, configuration, testing, and environment promotion.
Partner with Data Engineers and Data Quality Engineering to provide platform capabilities for automated validation and quality gates that can prevent downstream execution or publication when critical checks fail.
Improve release traceability, deployment consistency, rollback, and production readiness.
Enable metadata, lineage, and quality information to integrate with DataHub and monitoring platforms.
Cloud Platform & Infrastructure Automation
Build reusable Infrastructure-as-Code capabilities using Terraform.
Standardize deployment and configuration across AWS Glue, S3, EKS, MWAA, DataHub, and Grafana.
Develop consistent GitOps and CI/CD workflows using GitHub Actions.
Manage Kubernetes-based data-platform services using EKS, Helm, and source-controlled configuration.
Automate environment provisioning, configuration management, secrets, access controls, and infrastructure promotion.
Eliminate repetitive manual platform administration through automation.
Reliability & Observability
Own the operational health of shared data-platform services.
Build shared monitoring and observability capabilities using Grafana and CloudWatch across pipelines, data-platform services, Kubernetes, and supporting infrastructure, integrating database health signals provided by DBA-managed monitoring where appropriate.
Establish actionable alerts, runbooks, service-health measures, and escalation procedures.
Build platform-level rollback, disaster-recovery, and environment-recreation automation, partnering with the DBA on database backup, restore, failover, and recovery requirements.
Identify recurring operational problems and engineer permanent solutions.
Security & Governance Enablement
Implement least-privilege access, service identities, secrets management, and separation between individual and automated production access.
Partner with Security and Infrastructure teams on IAM, networking, vulnerability management, encryption, and privileged-access standards.
Support DataHub platform engineering and technical integrations for metadata, lineage, quality, and governance enablement.
Ensure infrastructure and platform changes are traceable, controlled, and auditable.
Engineering Enablement & Optimization
Build reusable templates, modules, deployment workflows, standards, and tooling for Data Engineers.
Lead data platform architecture decisions and evaluate trade-offs across reliability, performance, maintainability, security, and cost.
Mentor engineers in Data DevOps, CI/CD, Infrastructure as Code, database migrations, and production engineering.
Monitor platform utilization and identify opportunities to improve performance and cloud cost efficiency.
Basic Qualifications:
Bachelor’s degree an an accredited, not-for-profit, in-person University or College
A track record of commitment to prior employers.
7+ years of experience in Data Platform Engineering, Data Engineering, Software Engineering, DevOps, SRE, Cloud Engineering, or a related discipline.
Demonstrated experience building and operating production data platforms.
Hands-on production experience with Snowflake, including schema management, security, CI/CD and deployment automation.
Demonstrated experience implementing database schema versioning and automated migration frameworks.
Experience with Flyway, Liquibase, Alembic, or equivalent database migration tooling.
Experience implementing Snowflake CI/CD and schema deployment using schemachange or an equivalent approach.
Strong experience with Infrastructure as Code, Terraform, CI/CD, and AWS data platform services including Aurora/RDS, S3 and Glue.
Experience with dbt and Apache Airflow, preferably Amazon MWAA.
Production experience with Kubernetes, preferably Amazon EKS, and deployment tooling such as Helm.
Experience with monitoring and observability platforms such as Grafana and CloudWatch.
Strong scripting or software-development skills, preferably Python.
Strong understanding of data-platform reliability, security, deployment safety, backup, recovery, and production operations.
Ability to take ownership of complex platform problems and drive solutions from design through production.
Preferred Qualifications:
DataHub or similar metadata/catalog platforms
Advanced Snowflake security and governance
Data-quality and reconciliation frameworks
Schema and configuration drift detection
AWS Secrets Manager and advanced IAM patterns
Disaster recovery and environment recreation
Cloud cost optimization / FinOps
Production SRE or on-call experience
You do not need to be an expert in every technology in our environment. We are looking for strong Data Platform fundamentals, Data DevOps and platform engineering dept