GDPR Experts in Munich

Overall business responsibility for a program-wide initiative to create a central, authoritative data foundation for business customer master data (contacts and locations) within an IT service management transformation program.

• Managed the Epic portfolio from exploration through launch; prioritization and quarterly planning in a SAFe environment
• Aligned business units, architecture, and IT delivery around a shared vision and clear rules for data ownership (Data Governance)
• Prepared and secured scope and key decisions with program leadership, including deliberate descoping
• Managed risks, dependencies, and escalations; reported to program leadership and the PMO
• Developed the 2027 roadmap as a basis for budget and portfolio planning

Result: a clear MVP scope, key decisions made, and a 2027 roadmap. The program continued after handover without any loss of knowledge.

• Taught ML, BI, and Big Data to Master's students.

Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM

• Concept & IT implementation of inbound B2C campaigns, BPM process documentation
• Cross-functional implementation of several whitepapers / guides
• Setup of the customer journey with MS Dyn365 / CRM: Forms, landing pages, campaigns
• Project controlling, process documentation, testing and training / coaching, analytics reports
• Hands-on implementation & on-time launch of all campaigns for digital customer acquisition

• Managed Microsoft Cloud Accelerator Factory (CAF) programs for global enterprise customers, ensuring Azure cloud implementations aligned with security, governance, and compliance best practices, including ISO 27001-aligned controls and cloud security frameworks.
• Managed complex global enterprise transformation programs with strong focus on project delivery, financial governance, budget control, planning, risk management, and executive reporting, ensuring delivery within scope, timeline, and budget.
• Led the implementation of e-invoicing solutions for Nestlé, coordinating finance, IT, business stakeholders, and external providers to ensure successful integration, testing, rollout, and delivery of electronic invoicing processes.
• Managed an Oracle-to-PostgreSQL database migration, coordinating technical teams, application owners, testing activities, dependencies, risks, and cutover planning to ensure a controlled and successful transition.
• Led cross-functional programs involving finance and payment-related processes, enterprise platforms, and system integrations, with strong stakeholder management across business, IT, vendors, and senior leadership.
• Delivered transformation programs in FMCG environments, including Nestlé, managing complex international stakeholder structures, third-party providers, governance, RAID management, and business-critical dependencies.

AI telephone assistant platform

Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL

• Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
• Built agentic workflows and full automations with Claude Code and Google AI Studio.
• Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.

• Advise organizations on integrating AI into project and program management practices, delivering measurable productivity improvements
• Designed and implemented an AI agent to improve project communication, transparency, and reporting quality

• Project management for a simplification project to reduce effort for an IT transformation project
• Stakeholder management and preparation of decision documents for top management
• Scoping and PI planning across multiple delivery streams
• Planning requirements for the transformation project
• Creation of partner and customer journeys for the structured end-to-end capture of requirements
• Design of suitable tracking methods for project progress
• Coordination with IT service providers and transformation project committees

Topics:

• Further development of the CRM system NKAM and technical separation of “direct” and “indirect” sales
• Redesign of the discount management area and outsourcing to another system.
• Designing numerous improvements on the wholesale side to reduce manual effort down to the level of user stories.

• Planned and managed strategy and daily operations for cross-functional team with end-to-end testing and launch readiness responsibility, facilitating early product launches.
• Managed complex set of stakeholders including weekly alignments (60+ regular participants), communications, risk management and budget.
• Implemented AI solution that reduced documentation and testing automation time by 60%.
• Restructured team into agile processes and quarterly iterations, delivering 400+ high-quality features in 15 epics according to time and quality expectations.

• Built Azure Kubernetes clusters (AKS) with network policies, security groups, and RBAC
• Terraform-based infrastructure as code for secure, reproducible deployments in the BMW Azure cloud
• Hardened CI/CD pipelines with Jenkins, SonarQube, Fortify SSC, and Contrast AST
• Integrated SAP BTP/Kyma and ServiceNow GRC

• Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
• Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
• Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
• Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
• Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
• Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
• Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
• Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
• Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.

In my role as Senior Cloud DevOps Architect for BP, an oil and gas company, I had the mission to migrate the Electric Vehicle Charging platform of the EV Division from on-premises and Azure to AWS cloud, resulting in a hybrid multi-cloud, multi-tenant SaaS solution.

Deployment with Kubernetes for the application layer meant provisioning Kubernetes clusters managed by EKS and AKS, with a focus on integrating them into a multi-tenant environment. This integration was achieved by using Kubernetes namespaces and access controls to ensure data isolation and privacy enforcement.

In the database layer, we chose an RDS instance with PostgreSQL to support the backend infrastructure of our applications. Tenants shared the same RDS instance, but each had a dedicated schema.

To ingest near real-time data from physical charge points (CPOs), as IoT devices, via the OCPI protocol, we ran into significant delays with batch processing. As a result, we built a real-time streaming data pipeline using Apache Kafka, while prioritizing an event-driven architecture.

Led collaboration across multiple internal teams, external vendors, cloud providers, and on-site partners to integrate over five systems into a unified solution.

Achievements:

• Successfully designed and implemented hybrid multi-cloud solutions, integrating multiple cloud platforms (AWS, Azure) with on-premises infrastructure, using Site-to-Site VPNs, Firewalls, and Load Balancing.
• Led the migration of on-premises infrastructure to multi-cloud, multi-tenant infrastructure, resulting in 30% faster processing times.
• Migrated workloads from VMware and Hyper-V environments to cloud-based VMs, leveraging cloud-native services to optimize performance, cost efficiency, and scalability.
• Designed a multi-tenant Kubernetes platform leveraging the Kubernetes ecosystem, using Karpenter for dynamic EC2 node provisioning, KEDA for event-driven pod autoscaling (e.g., Kafka message lag), and Rancher for centralized monitoring of multiple clusters (EKS, AKS, or on-prem K8s), replacing Microsoft-centric Azure Arc management service.
• Designed and implemented Python-based FastAPI microservices as part of the EV core-backend on AWS EKS application layer, powering data ingestion and customer analytics pipelines.
• Developed asynchronous, event-driven APIs (Python-FastAPI) for real-time integration with CPOs, supporting OCPI 2.3 and OICP protocols.
• Designed and implemented a secure, production-grade Azure Databricks platform using Terraform, ensuring scalability and cost efficiency.
• Migrated on-premises ERP to a hybrid Dynamics 365 architecture with ERP hosted locally and CRM running in Azure, integrated via Azure Arc.
• Automated CI/CD pipelines for Databricks notebooks and jobs using GitHub Actions & Databricks CLI, reducing deployment time. Reduced infrastructure provisioning time by 70% by automating cloud resource deployment with GitOps.
• Ensured compliance with internal audit and data governance standards (GDPR) through OAuth2/OIDC-based authentication and fine-grained role-based access controls.
• Developed a Zero Trust security model, enforcing least-privilege access and microsegmentation, enhancing security posture and compliance with GDPR and NIST.
• Built interactive analytics dashboards in Amazon QuickSight, integrating data from S3 and Redshift to deliver real-time business insights and visualizations with embedded access for multi-tenant users.
• Led cloud security assessments and full-lifecycle cybersecurity integration during M&A, covering AWS, Azure, IAM (Entra ID), and data protection, while aligning security posture with NIST, ISO 27001, and GDPR across hybrid and cloud-native environments.
• Reduced cloud costs by 64% for a client's dev environment by implementing automated start/stop schedules for EC2 and RDS instances via AWS CDK with EventBridge Scheduler or AWS Systems Manager.

Tech stack:

• Infrastructure as Code: Terraform, AWS CDK, Ansible.
• Containers: Kubernetes on EKS, AKS, Docker.
• Streaming Data Processing: Kafka to Confluent Cloud, after AWS MSK.
• Frontend: TypeScript, React, NextJS, Hooks, Styled Components.
• Backend: Python with FastAPI, also Node.js with NestJS.
• Database: Aurora on PostgreSQL with TypeORM, RDS on SQL Server, Azure Databricks full setup and administration, ETL Pipelines.
• CI/CD and GitOps: GitHub Actions, Azure DevOps, ArgoCD.
• Monitoring and Observability: Prometheus and Grafana.
• Virtualization: Hyper-V, VMware Cloud on AWS, Azure Migrate.
• ERP Systems: Odoo, Microsoft Dynamics 365 Business Central on Azure, integrated with Azure Arc.
• Networking: Site-to-Site VPNs, AWS Direct Connect, Azure ExpressRoute, Firewalls (AWS Network Firewall, Azure Firewall).
• Security: IAM, NIST Framework, Zero Trust Security, AWS WAF, AWS Shield, GuardDuty.

GenAI – Chat & Voicebot

Setup of a GenAI solution with a knowledge base as well as chat and voicebots.

• Definition of use cases and chat/voicebot functionalities
• Project setup for cloud, knowledge base, LLMs and RAG
• AI guardrails, IAM concept
• Governance, Risk & Compliance (GRC)

Result:

Setup of an enterprise GenAI solution with knowledge base, chat/voicebots, IAM and governance.

• Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
• Two-gate governance: agent deliberation + mandatory human approval, complete signed audit trail; graduated autonomy model („internal → autonomous per skill“).
• Verified knowledge graph („Company Brain“) with source evidence for each answer; proprietary orchestration framework (Virtual Team Framework).
• Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
• Development of the governance-focused multi-agent platform TeamIntel (see AI reference projects).