Lead GCP Cloud Engineer

Mindlance is a company seeking a Lead GCP Cloud Engineer to support the Model Risk Management platform at Wells Fargo. The role involves managing and evolving the platform that enables statistical models to run at scale, as well as leading the design and deployment of cloud solutions using GCP and Apache Spark.

Responsibilities:

• Lead design, deployment, and management of OpenShift clusters or GCP projects supporting containerized Spark applications
• Architect and enhance the platform used for executing statistical risk models
• Drive platform modernization and cloud adoption initiatives
• Architect and oversee large-scale data processing workflows using Apache Spark
• Optimize Spark jobs for performance and cost efficiency using Kubernetes orchestration and auto-scaling
• Oversee integration of Spark with data sources (Kafka, S3/GCS, databases, data lakes)
• Lead development of Python-based microservices and backend tools (Django preferred) to support statisticians and data users
• Ensure scalability, usability, and reliability of tools and platform features
• Design and govern CI/CD pipelines in GitHub Actions, Sonar, Helm, Harness, etc
• Implement automation across deployments, environment management, and testing
• Monitor and tune cluster health, performance, and resource allocation using Prometheus, Grafana, and GCP tools
• Troubleshoot distributed and cloud-native system issues
• Ensure solutions follow enterprise security requirements
• Implement RBAC, encryption, and secure coding patterns
• Partner with data scientists, platform engineering, DevOps, and architecture teams
• Provide technical guidance and mentorship to junior and senior engineers
• Lead production deployments and root-cause analysis efforts

Requirements:

• 5–7+ years with Apache Spark for big data processing
• 3+ years with Python/Django backend development
• 3+ years building tools or platforms for high-volume data users
• 3–5+ years working with Google Cloud or equivalent cloud platforms
• 3+ years managing OpenShift/Kubernetes containerized workloads
• Proficiency in Spark frameworks (PySpark, Scala, or Java)
• Strong experience with Docker/Kubernetes concepts
• Hands-on OpenShift administration
• Experience with conda environments
• Strong coding in Python, Scala, or Java
• CI/CD exposure: GitHub Actions, Helm, Harness, Sonar
• Strong debugging skills across distributed systems
• Knowledge of GCP services (GCS, IAM, GKE, Cloud Run, etc.)
• Bachelor's degree in Computer Science, Engineering, or related discipline
• Lead Engineer: 8–10+ years with demonstrated leadership of complex platforms
• Experience supporting data-heavy financial or regulated environments