Data Private Cloud - Principle Engineer

Wells Fargo & Company•Iselin, NJ

1d•$159,000 - $305,000•Hybrid

About The Position

Wells Fargo is back in the office collaborating for fabulous outcomes! This role is a hybrid role and in the office three days a week. There is no visa sponsorships or visa transfers for this role. The role is positioned in the cities listed on the req. We’re seeking a Principal Engineer to drive the technical strategy, architecture, and delivery of our enterprise Data Private Cloud. You’ll lead end‑to-end platform design across our Kubernetes-based data ecosystem, enabling teams to migrate, build, and scale data engineering and analytics workloads on a modern, self‑service platform. This hands‑on leadership role spans full‑stack architectural oversight—from container orchestration to infrastructure-as-code—while serving as the senior technical authority for platform engineering teams and business partners.

Requirements

7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of hands-on experience with Kubernetes in production environments (OpenShift Container Platform strongly preferred)

Nice To Haves

Experience in financial services or other highly regulated industries
Experience with Kubernetes scheduling frameworks (YuniKorn, Volcano) for batch and AI workload optimization
Contributions to open-source projects in the data or infrastructure
Experience building and deploying applications with enterprise data sources
Hands-on experience with transformer architectures and fine-tuning open-source models
Professional certifications: CKA/CKAD, AWS/Azure/GCP Professional, Terraform Associate
Experience with GitOps practices (ArgoCD, Flux)
Background in platform product management or developer experience
Technical Expertise Infrastructure & Orchestration • Expert-level Kubernetes knowledge: deployments, stateful workloads, operators, CRDs, RBAC, network policies, storage classes
OpenShift Container Platform: Routes, SCCs, cluster administration, operator lifecycle management
Infrastructure-as-code with Terraform (modules, state management, provider development)
Container runtimes, image registries, and CI/CD pipeline integration
Data Platform Technologies • Apache Spark: architecture, tuning, Spark on Kubernetes, dynamic resource allocation
Distributed SQL engines (Trino, Presto) including federation and connector development
Apache Airflow: DAG design, executor configurations, Kubernetes executor
Data catalog and lineage tools (DataHub, Apache Atlas, or similar)
Apache Ranger or equivalent fine-grained authorization frameworks
Apache Iceberg or similar table formats; Hive Metastore operations AIOps Technologies • AIOps tools: anomaly detection with Prophet, PyOD, or custom models; log analytics with OpenSearch ML
Observability ML: Prometheus with recording rules, Grafana ML features, custom alerting models Security & Identity • Enterprise identity integration: LDAP, Active Directory, SAML, OIDC
Keycloak administration, realm configuration, and custom provider development
PKI, certificate management, and TLS termination strategies
Secrets management (HashiCorp Vault, Kubernetes secrets, external secrets operators)

Responsibilities

Technical Leadership & Architecture Own the architecture of the enterprise data platform (OpenShift, Kubernetes, modern data stacks)
Define platform standards for security, scalability, multi-tenancy, and operational excellence
Lead decisions around compute orchestration (Spark on K8s, YuniKorn), query federation (Trino, Kyuubi), and metadata management (Gravitino, Hive Metastore)
Design authentication/authorization (Keycloak, AD, Ranger)
Shape infrastructure strategy and open-source deployment patterns
Infrastructure & Platform Engineering Lead Terraform-based IaC and repeatable deployment practices
Architect networking, ingress, and service mesh configurations
Oversee PKI, SSL/TLS, and certificate lifecycle management
Build monitoring and observability strategies (OpenSearch, Prometheus, Grafana)
Ensure resilience through scheduling, quotas, and capacity planning
Implement GitOps for declarative deployments
Data Platform Components Provide leadership across: Compute: Spark on K8s, Kyuubi, JupyterHub Query/Analytics: Trino, Superset Orchestration: Airflow on Kubernetes Catalog/Governance: Gravitino, DataHub, Ranger Storage: Iceberg, S3/NetApp, PostgreSQL Messaging/Search: Kafka, OpenSearch
Security & Compliance Ensure compliance with regulatory requirements (OSFI, SOX, PCI-DSS)
Implement multi‑tenant isolation and robust security boundaries
Lead security reviews, threat modeling, and remediation
Partner with Security, Risk, and Compliance teams on audits and controls