AWS & Databricks Engineer @ Santa Clara, CA (Onsite)

Key Responsibilities

•     Architect and support AWS infrastructure for SAP workloads, including SAP S/4HANA, HANA, BW/4HANA, integrations, storage, networking, identity, backup, high availability, and disaster recovery.

•     Design and manage enterprise AWS services including VPC, Transit Gateway, EC2, EBS, S3, IAM, KMS, Route 53, CloudWatch, CloudTrail, AWS Backup, load balancers, and security services.

•     Define and govern Databricks architecture on AWS, including workspace strategy, network isolation, identity integration, Unity Catalog, S3-based data storage, cluster policies, job orchestration, and cost optimization.

•     Establish scalable data-lakehouse patterns for SAP and non-SAP data using Delta Lake, medallion architecture, Spark, Python, SQL, streaming, and batch pipelines.

•     Administer and support Informatica platforms, such as PowerCenter, IDMC/IICS, Data Quality, MDM, runtime environments, repositories, schedules, access controls, upgrades, patches, and operational monitoring.

•     Design secure, reliable integration patterns between SAP, Informatica, Databricks, AWS services, enterprise data sources, and downstream reporting or analytics systems.

•     Build and maintain Git-based CI/CD pipelines for infrastructure, Databricks assets, Informatica deployments, APIs, applications, and containerized workloads.

•     Implement infrastructure-as-code using Terraform, CloudFormation, Pulumi, or equivalent tools, with reusable modules and environment-specific promotion controls.

•     Architect, deploy, secure, and support Amazon EKS clusters and containerized application workloads using Docker, Kubernetes, Helm, Kustomize, Argo CD, Flux, or comparable GitOps tooling.

•     Establish DevSecOps controls, including code scanning, dependency scanning, container-image scanning, secrets management, automated policy checks, RBAC, encryption, and audit logging.

•     Implement platform observability through centralized logs, metrics, alerts, dashboards, and tracing using tools such as CloudWatch, Prometheus, Grafana, ELK/OpenSearch, Datadog, or Splunk.

•     Lead production support for high-severity incidents, conduct root-cause analysis, create remediation plans, and improve operational runbooks.

•     Define standards for availability, resilience, recovery objectives, patching, release management, change controls, capacity planning, performance tuning, and cloud-cost optimization.

•     Mentor engineering and operations teams, conduct architecture reviews, and communicate technical decisions to business and technology leadership.