Cloud Platform Engineer (DevSecOps & Data)

Industry: Automotive. Hybrid work location in Kraków (2-3 days per week from office).

• Strong AWS experience across compute, storage, networking, security, serverless, monitoring, and data services.
• Knowledge of Azure services such as Azure Functions, Event Grid, Service Bus, Data Lake Storage, Azure Monitor, Key Vault, Azure DevOps, GitHub integration, Synapse, Fabric, or equivalent services.
• Hands-on experience with Terraform, GitHub Actions, GitHub Apps, CI/CD design, GitOps practices, and automation frameworks.
• Experience with containerization and orchestration using Docker, Kubernetes, EKS, AKS, or similar platforms.
• Understanding of data lake/lakehouse architecture using Amazon S3 or Azure Data Lake Storage, AWS Glue Data Catalog, Apache Iceberg, Spark, EMR Serverless, Databricks, Synapse, or Fabric.
• Experience with databases and serving platforms such as PostgreSQL, OpenSearch, Neo4j, SQL engines, and analytics/reporting integrations.
• Strong understanding of event-driven architecture, queues, topics, event buses, workflow orchestration, APIs, and distributed system integration.
• Good understanding of cloud networking, DNS, certificates, private connectivity, logging, monitoring, and operational resilience.

Nice to have:

• AWS Solutions Architect, AWS DevOps Engineer, Azure Solutions Architect, Azure DevOps Engineer, or equivalent certifications.
• Experience in enterprise software engineering, automotive, embedded software, regulated environments, or large-scale engineering platforms.
• Experience with software engineering metrics, observability, data governance, security compliance, and reusable platform capabilities.

• Design, build, and operate secure, scalable cloud infrastructure across AWS and Azure.
• Develop and maintain DevSecOps automation, CI/CD workflows, reusable pipelines, infrastructure-as-code, and platform engineering services.
• Support data platform engineering across ingestion, transformation, governance, cataloging, quality, and serving layers.
• Build event-driven and serverless workflows using AWS Lambda, SQS, EventBridge, Step Functions, CloudWatch, and equivalent Azure services.
• Implement lakehouse patterns such as Landing, Bronze, Silver, and Gold data layers using object storage, catalogs, and distributed processing.
• Implement cloud security controls including IAM/RBAC, secrets management, encryption, audit logging, vulnerability scanning, and policy-as-code.
• Create technical documentation, runbooks, architecture diagrams, operating procedures, and engineering standards.