Description
We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience.
The Manager, Cloud & Data Platform Engineer owns the Retail Resource Center’s application and data technology stack in the Google Cloud environment, working in a fast-paced setting where reliability, security, data quality, and speed of delivery are critical.
Key Responsibilities
- Owns the application and data technology stack in Google Cloud, including architecture, availability, performance, and lifecycle management of Cloud Run services, Google Kubernetes Engine (GKE) clusters, Redis databases, BigQuery datasets, and supporting services.
- Manages code deployment and release processes, designing, building, and maintaining CI/CD pipelines for application and data workloads.
- Oversees containerization and deployment practices, including configuration management and container image lifecycle management.
- Designs, builds, and maintains batch and streaming data pipelines that ingest data into BigQuery.
- Develops and manages the analytics data layer in BigQuery, including dataset design, and SQL-based transformations.
- Implements data quality checks, schema management, lineage, and pipeline observability.
- Applies data governance and security controls, including dataset- and column-level access, handling of sensitive data, and retention policies.
- Partners with analysts, product owners, and business stakeholders to translate reporting needs into reliable datasets and dashboards.
- Defines and manages infrastructure as code with version-controlled, peer-reviewed changes.
- Implements monitoring, logging, tracing, and alerting for applications, infrastructure, and data pipelines.
- Leads incident response, root cause analysis, and post-incident reviews for production issues.
- Manages IAM roles, service accounts, network configuration, secrets, and vulnerability scanning.
- Plans for capacity, autoscaling, backup, and disaster recovery for applications and data stores.
- Collaborates with software engineering, security, and operations teams to understand requirements and develop solutions.
- Leverages AI to accelerate development and automation across application, infrastructure, and workloads.
- Develops AI agents to automate workflows and operational tasks.
Required Qualifications
- 3+ years of experience in DevOps, site reliability, cloud, platform, or data engineering.
- Working knowledge of Google Cloud services, including Cloud Run, GKE, Redis, BigQuery, and IAM.
- Strong understanding of Kubernetes and Docker.
- Experience with infrastructure as code and CI/CD pipelines.
- Proficiency in at least one scripting or programming language (e.g., Python) and strong SQL skills.
- Experience leveraging AI tools to support development and automation.
- Experience designing and operating data pipelines and ETL/ELT workflows.
- Strong problem-solving, troubleshooting, and decision-making skills.
- Clear written and verbal communication skills.
Preferred Qualifications
- Google Cloud certification (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer, or Professional Data Engineer).
- Experience with GitOps tooling, event-driven architectures, or API gateways.
- Experience with Cloud Composer/Airflow and BI tools such as PowerBI.
- Experience developing AI agents to automate workflows and accelerate delivery.
Benefits
- Medical, dental, and vision coverage.
- Paid time off.
- Retirement savings options.
- Wellness programs.
Pay Range
$54,300.00 - $145,860.00