Responsibilities: Data Platform & Data Dev

Ops Own the Data Dev

Ops 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 Data

Hub 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, Data

Hub, and Grafana .

Develop consistent Git

Ops and CI/CD workflows using Git

Hub 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 Cloud

Watch 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 Data

Hub 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 Dev

Ops, 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, Dev

Ops, 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 Cloud

Watch .

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: Data

Hub 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 / Fin

Ops 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 Dev

Ops and platform engineering depth, and the ability to take ownership across a modern enterprise data ecosystem .

Success means creating a platform where: AWS RDS/Aurora and Snowflake changes are versioned, tested, automated, and recoverable through standardized deployment frameworks. dbt and Airflow workloads move consistently across environments.

Quality failures can prevent incorrect data from being published.

Infrastructure and platform configuration are reproducible from source control.

Manual production changes and repeated operational work are progressively eliminated.

Platform services have actionable monitoring and tested recovery procedures.

Reliability, security, performance, and cost are continuously improved.

Data Engineers spend more time building data products and less time managing infrastructure and deployment mechanics.

What's in it for you? When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed.

We offer you generous compensation and performance-based incentives.

CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement.

Our benefits package includes (but is not limited to): Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug Life, legal, and supplementary insurance Virtual and in person mental health counseling services for individuals and family Commuter and parking advantages 401(K) retirement plan with matching contributions Employee stock purchase plan Paid time off Tuition reimbursement On-site fitness center and/or reimbursed fitness center membership costs (location dependent) Access to CoStar Group’s Employee Resource Groups Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks The final salary or hourly rate offered for this role will fall within the range set forth below based on a variety of factors, including but not limited to, geographic location, skills, and competencies.

Base Compensation: CAD $140,000-$170,000 (annually)

📌 Senior Data Platform Engineer - Zonda - Toronto, Ontario
🏢 CoStar Group
📍 Toronto