Senior Software Engineer
$101.97k - $203.94kCVS Health
We're building a world of health around every individual - shaping a more connected, convenient and compassionate health experience. At CVS Health®, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger - helping to simplify health care one person, one family and one community at a time. Position Summary: We are seeking a highly skilled backend-focused Senior Software Engineer to join our modernization team focused on transforming the legacy CVS pharmacy systems into a cutting-edge, cloud-native platform. As part of the team, you will play a crucial role in designing and developing microservices that drive the modernization of critical patient and drug domains. You will work on integrating cloud-native solutions, enhancing performance, and ensuring seamless operation within a highly scalable and secure environment. The ideal candidate will have extensive experience in backend development, system design, and a strong understanding of cloud-native software engineering principles. Responsibilities:
- Design, build, and maintain scalable data pipelines to support analytics, ML, and operational reporting
- Develop robust data ingestion, transformation, and integration workflows using Python, SQL, and modern data engineering frameworks
- Build and maintain batch and streaming data pipelines leveraging technologies such as Kafka (or similar pub/sub tools)
- Work with Google Cloud Platform (GCP) services, including Cloud Storage, Dataflow, Pub/Sub, BigQuery, Cloud Spanner and Cloud Functions
- Develop and manage data APIs and interfaces (REST and GraphQL) to enable high-performance data access across microservices
- Implement CI/CD automation for data pipelines using GitHub Actions, Argo CD, or equivalent tools
- Collaborate with Data Scientists and MLOps teams to integrate ML/NLP models into data pipelines and production workflows
- Build and operationalize NLP data pipelines for structured and unstructured data sources (e.g., Rx claims, clinical documents)
- Implement frameworks for observability and data quality, ensuring ML predictions, confidence scores, and fallback events are logged into data lakes or monitoring systems
- Design and provision cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform or Pulumi for GCP resources including GKE clusters, Cloud SQL, VPC networks, IAM, and storage
- Deploy, configure, and manage containerized data workloads using Kubernetes (GKE) - including deployments, autoscaling (HPA/VPA), namespaces, resource quotas, and health checks
- Architect and maintain network topology for data platform environments - VPCs, subnets, firewall rules, private service access, Cloud NAT, and VPC Service Controls
- Implement and enforce IAM policies, service account governance, and secrets management (GCP Secret Manager or HashiCorp Vault) to ensure least-privilege access across all data services
- Build and maintain infrastructure monitoring and alerting using Cloud Monitoring, Prometheus, Grafana, or equivalent - covering pipeline latency, throughput, error rates, and resource utilization
- Establish and maintain CI/CD pipelines for infrastructure changes using Terraform Cloud, GitHub Actions, or Argo CD, ensuring infrastructure drift detection and rollback capability
- Manage environment parity (dev/staging/prod) for data platform infrastructure, including environment-specific configuration management and promotion workflows
- Drive cloud cost governance - right-sizing compute resources, implementing committed-use discounts, setting up budget alerts, and producing cost attribution reports per workload
- Design and implement disaster recovery, backup, and high-availability strategies for data stores, pipeline infrastructure, and ML serving endpoints
- Collaborate with Security and Platform teams to ensure data infrastructure compliance with enterprise security policies, SOC 2, HIPAA, and CVS Health regulatory requirements
- 5+ years of experience building data pipelines or backend data workflows using Python, Java, or similar languages
- 2+ years of experience designing REST/GraphQL data services or integrating data APIs
- 2+ years of experience with cloud platforms (GCP, AWS or Azure)
- 2+ years of hands-on experience with Infrastructure as Code tools (Terraform preferred; Pulumi or CDK)
- Hands-on experience working with ML/AI model integration in production (e.g., Vertex AI Endpoints, TensorFlow Serving, ML REST APIs)
- Experience handling structured and unstructured datasets, including healthcare data (Rx claims, clinical documents, NLP text)
- Direct, hands-on experience with Google Cloud Platform, especially BigQuery, Dataflow, GKE, Composer and Vertex AI
- Knowledge of GenAI pipelines, LLM prompt workflows, and agent orchestration frameworks (e.g., LangChain, transformers)
- Experience deploying Python-based ML/NLP services into microservice ecosystems using REST, gRPC, or sidecar architectures
- Familiarity with GCP Shared VPC, VPC Service Controls, or private Google Access configurations for secure data platform networking
- Exposure to FinOps practices - cloud cost attribution, showback/chargeback models, and resource tagging strategies
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