Site Reliability Engineer (SRE)

The service to be provided will be part of Data integration team working on integrating applications within different business areas of Siemens Digital Industries, specifically focusing on Deliver Chain. The Data Streaming platform is based using an event driven architecture and leveraging tools available on Siemens technological landscape like Apache Kafka (Confluent), Kong and Flink.

This role as Site Reliability Engineer focuses on maintaining, scaling, and optimizing the infrastructure and operations that support our data integration pipelines by working with cloud technologies, automation tools, and monitoring systems to ensure reliable, scalable, and efficient platform operations.

Their daily tasks will be distributed along three main topics: Infrastructure & Cloud Operations (e.g., Design and maintain AWS cloud infrastructure using Infrastructure as Code (Terraform); Manage and optimize cloud resources including compute, storage, and networking;), CI/CD & Pipeline Operations(e.g., Build and maintain CI/CD pipelines for data platform deployments, automate deployment processes and configuration management;)and Platform Reliability & Monitoring (e.g., Design and implement observability frameworks using metrics, logs, and distributed tracing; Build custom monitoring solutions and instrumentation for data pipelines and infrastructure;).

Mid-Level - DevOps experience, preferably as site reliability or infrastructure roles

Mid-Level - AWS Cloud Expertise - EC2, S3, RDS, VPC, IAM, CloudWatch (preference to AWS certificates)

Mid-Level - Cloud APIs to automate provisioning, deployment, improving system performance and infrastructure scaling (terraform, kubernetes, docker, Ansible or similar configuration management)

Mid-Level - Programming skills, Python for automation scripts and infrastructure tooling

Mid-Level - CI/CD Systems - Jenkins, GitLab CI, GitHub Actions, or similar platforms

Mid-Level - Version Control: Git workflows and branching strategies

Mid-Level - Monitoring and Observability: CloudWatch, Prometheus, Grafana, or similar observability tools

Mid-Level - Experience with data platform infrastructure and database operations : databases (relation and nonrelational), data Structures (json, xml) and using SQL

Mid-Level - Streaming platforms: Kafka cluster management and operations