Senior Data Platform Engineer: Cloud DataOps Snowflake

CoStar Group, Inc.

Toronto

On-site

CAD 140,000 - 170,000

Full time

5 days ago

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Benefits offered by this job

Healthcare coverage (Medical / Vision)

401(K) retirement plan with matching

Tuition reimbursement

On-site fitness facilities

Stock purchase plan

Job summary

CoStar Group is seeking a Senior Data Platform Engineer in Toronto to design, automate, and operate the shared data platform capabilities across Snowflake, AWS, and containerized services. You will own platform automation, CI/CD patterns, and reliability, collaborating with Data Engineers, Security, and Infra teams to ensure scalable data products and production readiness.

The role requires 7+ years in data/platform engineering and hands-on experience with Snowflake, Terraform, Kubernetes,

Qualifications

Bachelor’s degree or equivalent with 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 include 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.

Responsibilities

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.
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.
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.
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.
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.
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.