Google Cloud Certified - Associate Cloud Engineer

Project: SCS (Settlement / Clearing Services)

Settlement platform serving multiple trading and clearing venues — counterparty risk safeguarding, settlement volume reduction, central risk management, and post-trade anonymity.

Technologies: Java 17, Spring Boot 3, Microservices, Spring Data JPA, SonarQube, Fortify (SCST), Mockito, Jenkins, OpenShift, Maven, Podman, GitHub, JIRA, Liquibase, Swagger, AMQP, Apache Camel, Terraform, PostgreSQL, Instana, Graylog.

• Identified and remediated CVEs in third-party libraries using SCA tooling, strengthening the security posture of production components.
• Maintained 90% code coverage with SonarQube, improving code quality and reducing production defects.
• Enabled mTLS for database authentication and message broker connections, enforcing encrypted, certificate-validated communication.
• Designed and deployed microservices with asynchronous, REST-based communication between components.
• Optimized a high-volume REST API (~200K requests) by reducing response time from 3s to 2s (33% improvement), boosting throughput and reliability under production load.
• Automated build and continuous integration pipelines using Maven and Jenkins.
• Orchestrated containerized workloads on Podman/OpenShift and governed schema evolution with Liquibase, ensuring reliable, repeatable deployments across all environments.
• Optimized Java code and implemented EHCache-based caching, improving application performance.
• Streamlined release management by governing application images, JAR versions, and dependencies through DBAG Artifactory, ensuring version consistency and audit traceability across environments

Clients: CARIAD, AUDI AG

• Built and deployed enterprise MLOps pipelines using Azure Machine Learning and Databricks. Reduced model release cycles by 95 percent, from four weeks to two days, through automated CI CD workflows.
• Delivered cloud native DevOps platforms for ADAS programs using Azure data services, Kubernetes, and Terraform based infrastructure provisioning.
• Designed high availability architectures with automated failover. Cut system downtime by 85 percent for mission critical energy trading platforms.
• Developed and integrated AI agents and enterprise chatbots using LangChain, AutoGPT, and GPT models. Enabled autonomous workflows and decision driven automation.
• Reduced cloud infrastructure spend by 40 percent through autoscaling strategies, spot instance usage, and policy driven resource governance across Azure and AWS.
• Partnered with Data Scientists, ML Engineers, Product Managers, and executive stakeholders to deliver large scale automotive and energy solutions.
• Implemented GitOps driven CI CD pipelines supporting automotive software delivery for over 500 engineers across distributed product teams.
• Designed and operated Kubernetes platforms on Azure AKS. Improved deployment stability and reduced rollback events by 70 percent.
• Implemented observability and monitoring stacks using Prometheus, Grafana, and Azure Monitor. Achieved 99.9 percent service availability targets.

• Cloud Computing Fundamentals & Architecture: Expertise in core cloud concepts, including the three main Service Models (IaaS, PaaS, SaaS) and diverse Deployment Models (Public, Private, Hybrid, Multi-cloud).
• Modern Application Deployment Strategies (GCP Focus): Instruction on the GCP Application Hosting Spectrum, covering Virtual Machines, Containers (Kubernetes and Cloud Run), Platform as a Service (App Engine), and Serverless Computing (Functions as a Service - FaaS).
• Data Management & Big Data Analytics: Comprehensive coverage of Cloud Storage options (Object, Block, File) and Database solutions, including Relational (Cloud SQL), NoSQL (Firestore, BigTable, Memorystore), and serverless enterprise data warehousing (BigQuery).
• DevOps and Infrastructure Automation: Skills in DevOps principles, including Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as Code (IaC) using tools like Terraform, and implementing effective Monitoring and Logging for system observability.
• Emerging Technologies & Responsible Cloud Use: Focus on crucial topics like Cloud and IoT Security, Identity and Access Management (IAM), data privacy, and the ethical considerations of cloud and massive data collection.

• Building the strategy and managing the company.
• Consulting on cloud technologies with a focus on AWS and Kubernetes.
• Leading automation projects and CI/CD pipeline implementations.

• Extended a global large-scale project to improve the multi-tenant GCP data platform using FAST framework concepts, leveraging Terraform, Terraform Enterprise, and GitLab.
• Collaborated closely with security and governance teams to architect and implement secure and compliant GCP environments, focusing on VPC Service Controls, KMS, organizational structure, and guardrails to support the isolation of corporate entities.
• Enhanced the security posture of the enterprise GCP platform by implementing robust security measures, including GCP organization policies, deny policies, and VPC Service Controls to safeguard against potential exfiltration risks.
• Implemented controls based on CSA Cloud Controls Matrix (CCM v4) to secure the GCP cloud environment.
• Automated key components of the GitLab CI/CD pipeline by integrating OpenID Connect (OIDC) for workload identity federation, necessary for a large migration from GitHub.
• Implemented a YAML-based project factory to facilitate easy, secure, and governed provisioning of tenant projects, increasing speed, scalability, and usability while minimizing operational burden.
• Developed a dynamic approach for policy attachment to tenants using a YAML-based custom IAM template approach.
• Evaluated and implemented Google PAM (Privileged Access Manager) in a proof of concept for organization-wide just-in-time access.
• Set up CyberArk SCA and CEM tooling to ensure secure cloud access and provide visibility into the cloud environment.
• Handled GCP incidents, ensuring prompt resolution and operational stability.
• Authored and maintained extensive documentation within an Agile environment, utilizing Jira and Confluence for project tracking and knowledge management.
• Utilized HashiCorp Sentinel as a policy-as-code tool to shift-left cloud security by enforcing policies before infrastructure provisioning.
• Used Prisma Cloud to continuously monitor and secure GCP resources, ensuring compliance and risk mitigation across the organization.
• Developed a custom Org Policy Factory to standardize and automate custom governance across projects, ensuring enforcement of non-trivial organizational controls.
• Architected and built a cloud-agnostic credential lifecycle management platform with Python and GitLab to automate the secure handling of static credentials, improving governance, compliance, and audit readiness.
• Delivered an executive-level presentation on VPC Service Controls to C-level stakeholders, driving strategic awareness and alignment on cloud security posture.
• Led resolution of P1 incidents with high production impact, restoring services under critical time constraints.
• Architected and deployed a central monitoring and alerting solution using Cloud Monitoring and PromQL, providing real-time visibility into system health and proactive incident detection.
• Designed and developed a Python-based broker for self-service integration with an internal developer platform, streamlining onboarding and reducing manual effort.
• Implemented a templating approach for VPC Service Controls, enabling repeatable, secure, and consistent deployment patterns across tenants and environments.

• Architectural Design of GCP Infrastructure Models
• Consultant for Strategic Migration Decisions
• Lead Engineer for Platform Automation
• Lead Engineer for Deployment of New Applications

• Evaluation of RAG for legal advisory (build or buy)
• Evaluation and POC of RAG for an ERP time tracking module
• Consulting on foundation model selection
• Setup AI development environment (eliminating shadow AI)
• AI strategy consulting
• AI-assisted code creation and context engineering make change sets larger
• Strong software engineering expertise, code reviews and safeguarding through pipelines and domain-specific automated test cases