Google Cloud Storage Experts in Germany

• Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
• Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
• Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
• Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
• Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
• Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
• Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
• Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
• Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
• Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment

I implemented a Zero-Trust architecture for robust, military-grade maritime container mini data centers based on VMware & Tanzu to support containerized GIS workloads for ground forces. The main focus was on securing communications, workload protection, and data access in contested electronic battle environments affected by jamming, interception, signal manipulation, and constantly changing operational conditions. I designed and architected use cases so that every element of workload, identity, and system could continue to operate independently and securely even in degraded or disrupted scenarios. In parallel, I defined the enterprise and solution security architecture with LeanIX, Bizzdesign, and HOPEX as enterprise architecture, repository, and governance platforms to maintain architecture inventory, relationships, traceability, target pictures, and security governance in complex environments. For the architectural designs, I used Sparx Enterprise Architect to describe formal architecture views, interfaces, trust boundaries, and system architecture in both IT and OT environments. IriusRisk was used for threat modeling of the solution to identify architecture-driven risks, derive security requirements, and detect countermeasures and design gaps directly from the solution models. Risk and compliance management was supported with Archer. Architecture decisions, control gaps, and operational risks were translated into controlled governance and auditable compliance measures. For documentation, collaboration, and visual design, I used Confluence to maintain Architecture Decision Records, Security Blueprints, and workflows. I used Lucidchart and draw.io to create design artifacts tailored to stakeholders. I also defined OT security concepts with support from electrical and mechanical engineers in the areas of oil, vehicle onboard systems, rail, power plants, pharma, gas turbines, and nuclear technology. I created the end-to-end OT security strategy, starting with global policy, developed into standards and procedures, and finally aligned with Bell-LaPadula, Purdue Model, SABSA, TOGAF ADM, CENELEC 50701, IEC 62443, and NIST standards. In addition, I worked with engineering team leads to identify critical KBP assets and place them under protective measures that segmented SCADA, PLC, and HMI assets. I drove collaboration between Security, IT, and OT teams to create standardized workflows and use cases for the OT security solution catalog, while integrating Defense-in-Depth and Zero-Trust principles into operational environments. A key part of my work was integrating multidisciplinary engineering, security, and operations stakeholders into a unified security blueprinting strategy and ensuring that architecture, threat modeling, governance, and documentation were technically strong and operationally practical.

• Conducted Excel trainings and supported the reorganization and setup of cost controlling in wholesale trade.
• Excel training content: spreadsheet setup, data validation, date calculations, logical formulas (IF & IFERROR), lookup functions (VLOOKUP & XLOOKUP), name manager, error checking, grouping, file, workbook and sheet protection, sorting and filtering, subtotal calculations, pivot tables, Get and Transform (Power Query), Power Pivot, formulas and functions, creating links (GETPIVOTDATA).
• Review of the existing data structure, organization and creation of improvement suggestions.
• Support in implementing all measures.
• Answering questions about MS Excel.

• Led bankable technical and commercial due diligences and IT carve-outs across hospitality, TIC energy, SaaS, and FMCG
• Conducted comprehensive IT assessments for mid-market companies across the DACH region
• Created pitch decks and sales materials driving new client acquisition in large-cap transactions
• Managed customer-facing projects with complex stakeholder landscapes, providing CIO support in project management, portfolio management, and coaching

• Implementing applications with Kotlin and Ktor as microservices
• Using MongoDB in the MongoDB Atlas cloud
• Asynchronous communication of services via Google Pub/Sub
• Using Kotest and MockK for unit tests
• Developing an administration frontend with TypeScript, React and Express.js
• Provisioning environments in GCP using Terraform
• Implementing CI/CD processes with GitHub Actions
• Operating scalable production and test environments in GCP with Kubernetes, Helm and Flux CD
• Monitoring environments with Prometheus and Grafana
• Providing BI data in the Google BigQuery data warehouse

• Architected ETL services for event-driven data exchange between enterprise systems on a Kafka streaming backbone.
• Optimized CI/CD pipelines for Azure AKS deployments and improved OpenSearch monitoring and alerting for proactive incident detection.

Tech: Java / Kotlin, Quarkus, Kafka / Avro, Azure / AKS, Azure Storage Container, ArgoCD, GitLab CI, OpenSearch, Terraform

• 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.

• A warehouse valuation system was reimplemented using Java, Spring Boot, and Camunda. The backend solution focuses on integration and batch calculations, the frontend on managing formulas and reviewing results.
• Java 21
• Spring Boot
• JPA
• Maven
• REST
• Kafka
• PostgreSQL
• DB2
• Liquibase
• Google Cloud Storage
• Keycloak
• GitLab CI/CD
• Helm
• Terragrunt
• SonarQube
• Angular
• IntelliJ
• JUnit 5
• Mockito
• Open API

• Integrated complex AI-based energy system models into the frontend framework, enabling the visualization of insights for 6+ key clients and maximizing energy utilization.
• Maximized energy efficiency and utilization by architecting the seamless data flow between AI models and the user interface for rapid, actionable reporting.

• IAUP (Interregional Academy of Personnel Management) commissioned the development of a distance learning system for its secondary school subdivision.
• Development of the website [link]
• Development of a billing system and integration with various payment systems
• Development of a distance learning system based on the open source Moodle solution
• Integration of the distance learning system into the user office on the [link] website
• Front-end: Vue.js v2, Nuxt.js, JavaScript, HTML, CSS, SCSS
• Back-end: LAMP (Linux, Apache, MySQL, PHP), PHP Framework Laravel, Redis, Swagger, MySQL 8.x, PayPal API
• DevOps: Docker, CI/CD, GIT

• PRISMA project
• Ansible automation
• Windows third level support for Windows NT, Windows 2000, Windows 2013, Windows 2016, Windows 2019

• Mobile: Kotlin Multiplatform (KMP), Kotlin, Swift, SwiftUI, Jetpack Compose, Ktor, Room, Koin
• Backend: Spring Boot, GCP Cloud Run, GCP Load Balancer, GCP Eventarc
• Planned and developed a cloud backend architecture with Google Cloud Platform
• Developed a cross-platform architecture with Kotlin Multiplatform (KMP)
• Tech lead for comprehensive large project including webshop, two apps and omnichannel backend

• Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
• Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
• Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
• Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
• Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
• Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
• Supported development and maintenance of IT strategy aligned with business requirements
• Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
• Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
• Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
• Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
• Developed a two-year infrastructure technology roadmap yielding 25% cost savings
• Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics