Microsoft SQL Server Experts in Germany

• Founder of CheironX: AI-supported GRC management (ISO 27001, BSI IT-Grundschutz, TISAX, DORA)
• Strategic focus on Agentic AI and GenAI for modern IT Governance, Risk & Compliance Management
• IT interim management and strategic consulting

• Architected, Deployed and Supported hosted email solutions in Linux and Windows environments with enterprise-grade anti-spam and security architecture for service-provider environments.
• Managed Microsoft Azure environments including Virtual Machines, VNets, Storage, VPN, and Firewall configuration.
• Administered Microsoft Exchange Server (2010-2019), Microsoft Exchange Server SE, Active Directory, PKI, Hyper-V and Zimbra environments with disaster recovery planning and operational support.
• Led Microsoft 365 onboarding and migration projects from Exchange, IMAP, and Zimbra platforms to Microsoft 365.
• Prepare security and compliance to support Microsoft 365 Copilot.
• Implement information protection and data loss prevention by using Microsoft Purview.
• Implement retention, eDiscovery, and communication compliance in Microsoft Purview.
• Integrated Active Directory Domain Services (AD DS), Active Directory Certificate Services (AD CS), and Active Directory Federation Services (AD FS).
• Delivered secure hybrid infrastructure solutions integrating Microsoft Windows Server and Linux-based enterprise environments.
• Supported enterprise integration projects involving Debian, Ubuntu, CentOS, Red Hat, Barracuda ESG, Qmail and Zimbra Platforms.

• Operation and further development of the network and security infrastructure.

• Monitoring, analysis and resolution of network and security incidents.

• Cross-departmental collaboration with other teams on operations and further development, and reporting.

• Firewall vulnerability analysis.

• Firewall access requests.

• Troubleshooting IP communication issues on network and firewall infrastructure.

• Security-critical IT infrastructure, processing of personal data, compliance with legal requirements.

• Products: Palo Alto Networks Firewalls, Cisco ACI, Checkpoint Firewalls, F5

• Technologies: SDN, SDWAN, Cisco EPIC, Cisco ACI

• Creating concepts and architecture for domain integration (SEAT into the VW structure)
• Domain trusts and administration
• Operation and administration of Windows 2022/ 2025 servers and domains
• Domain restructuring
• GPO and SG editing and migration
• DNS restructuring and migration

Technologies: Windows 2022, Active Directory, ADFS, AD Azure Connect, DHCP, DNS, GPO, VMWare vSphere, Hyper-V, Powershell, Jira, MS Office 365,), SCCM, VSAN Fileservices, Approximately 800 servers, 400 users

• Extension of a Swing-based UI for recording Security Restricted Articles during baggage screening.
• Introduction of a new workflow for recording Deboarding Events.
• Extension of the reporting system for Security Restricted Articles and Deboarding Events.
• Implementation using JBoss Wildfly, PostgreSQL, spring-boot 3.x, Java 8/21, Swing, JSF, JAX-RS/Resteasy, Docker, Maven, Kiro.

Project – Evaluation and development of databases for a new product line for a measuring equipment manufacturer

• Current-state analysis
• Requirements analysis of the data storage layer
• Writing benchmark tests
• Design of the new database schema
• Database migrations
• Development of audit logging and Part11
• Creation of backup and recovery concepts
• Design of the persistence layer API
• Writing unit tests
• Creating requirements in Azure

Tools: C#, Visual Studio 2022, Azure DevOps, SonarQube, Git, RestSharp, WebServer, PostgreSQL, MS SQL, SQLite, MinIO, Podman, Docker, DataGrip, SQL Management Studio, HeidiDB, pgAdmin

Working Environment

• Insurance / Claims Management (Property, Liability, Automotive)
• REST-based ClaimAPI with Guidewire ClaimCenter

Scope

• Further development of the internal REST-based ClaimAPI with Guidewire ClaimCenter as the backend and various portals/front-end offices as clients, and with the following objectives: + increased AI-supported claims processing outside of Guidewire ClaimCenter + and support for all lines (property, liability, automotive).
• Further development of automated claims processing

Activities

• Interfacing IT & Business
• Design activities with documentation in Confluence, Jira: + Requirements engineering (functional and non-functional) + Design of REST endpoints and coordination with interface partners (esp. AI-colleagues) + Identification, design and evaluation of alternative solutions (moving away from a monolithic approach toward fine-grained endpoints, with code reuse across all lines if possible) + Creation / refinement of product backlog items in Jira, i.e. epics, user stories and tasks, incl. alignment with developers & POs during (pre-)refinement sessions + Using AXA Secure GPT when creating / refining user stories (description, acceptance criteria) and designing REST endpoints + Estimation and prioritization of user stories and tasks during Sprint Planning sessions + Coordination and support during the implementation of Product Backlog items + Driving decision making with preparation and presentation of decision-making documents
• Quality assurance: + Test management, including test case creation using Xray in Jira + Test execution using Bruno as REST client and in Guidewire ClaimCenter + Submission of test artifacts for PO approval + Analysis of production bugs

Methods Big Room Planning (aka PI-Planning in SAFe), Scrum, BPMN, EPK, UML, ERM, DDD

Tools / Tech Stack Teams, Confluence, Jira with Xray, OpenAPI/Swagger, REST, JSON, XML, MS Office, Bruno, GitHub repository (reading), Guidewire ClaimCenter, AXA Secure GPT (AXA's in-house GenAI solution based on Azure OpenAI)

As part of preparing and providing operational support for a company succession:

• Company analysis: Analysis of the overall economic, organizational and structural situation (current status, strengths/weaknesses, potential risks)
• Process analysis: Recording and documentation of all relevant business processes (BPMN, UML) in the areas of management, finance, purchasing, sales and operations
• Process optimization: Identification of weaknesses and inefficiencies, development and operational implementation of improvement measures
• Stakeholder management: Identification and analysis of all relevant internal and external stakeholders; structured communication and coordination with former and future owners, shareholders and employees
• Change management: Supporting employees and management throughout the handover process; building acceptance and trust among all parties involved
• Governance & documentation: Preparation and handover of structured operating manuals, process documentation and an organizational manual for the new business owner
• Risk & weakness analysis: Assessment of operational and strategic risks in the handover process and development of recommendations for action
• Operational support: Interim assumption of management responsibilities; ensuring business continuity during the transition phase

• Designed and developed a production-ready data platform based on Microsoft Fabric for an e-commerce company
• Built a scalable Medallion Architecture (Bronze, Silver, Gold) with Lakehouse and Delta Lake as the foundation for analytics and AI applications
• Developed a metadata-driven ETL platform with PySpark and a generic Incremental Loading Framework (SQL Server → Bronze → Silver → Gold)
• Developed reusable components for Microsoft Fabric Notebooks to standardize data integration, transformation, and validation
• Implemented automated data pipelines including monitoring, logging, error handling, and Delta MERGE strategies for stable production operations
• Built a business layer architecture for reporting, data warehousing, and reusable data products
• Integrated heterogeneous data sources via SQL Server, REST APIs, Amazon SP API, and Google Analytics 4
• Worked closely with business departments to analyze business requirements and translate them into scalable data architectures

Technologies: Microsoft Fabric, PySpark, Python, SQL Server, Delta Lake, Lakehouse, OneLake, Data Factory, Data Warehouse, REST APIs, Amazon SP-API, Google Analytics 4

Development of AI and traditional models to analyze medical and patient data, including medication analyses, diagnosis analyses, forecasts, procedure analyses, dosage analyses, comorbidity analyses, prescription analyses, patient potential analyses, referral profile analyses, and prescription analyses. Analyses in the field of Real World Evidence.

Healthcare IT, pharmaceutical industry

Tasks, responsibilities:

• Gathering customer requirements
• Planning the subproject
• Designing and defining KPIs
• Designing and developing models and visualizations of results using customer dashboards
• Developing and implementing data warehouse adaptations
• Deriving recommendations for action

Methods, technologies:

• Simulation
• Artificial intelligence
• Python
• R
• SQL
• Microsoft Power BI
• Amazon Web Services
• Elasticsearch
• PostgreSQL
• Databricks
• Multivariate statistics

Product:

• Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
• Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
• Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
• Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
• Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

• Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
• Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.

Further Development of the Integrated Capacity Management Platform InKa

Rail Infrastructure

• Power BI shared datasets and reports via DirectQuery on Amazon Redshift (timetable, construction and capacity data)
• Automated report testing with Playwright in Docker containers, version control with GitLab
• Concept and implementation of user communication (information page, changelog, known bugs)

Initial Situation:

The integrated capacity management platform (InKa) is a monitoring and analysis platform for data from timetable and capacity management: customer orders, infrastructure, timetable operations, construction, as well as route capacity and width. The data is stored and linked in a structured data warehouse. This makes it possible to create complex KPIs across different source systems and display current and future route utilization as well as construction activity across the network. The goal is to improve strategic, medium-term and intra-year planning and provide users with easy access to capacity management analyses.

Measures:

• Enablement: Introduction of Power BI with training and workshops for development teams.
• Consulting & Design: Problem analysis, concepts and solution consulting for reporting requirements; implementation of reporting solution plans.
• Data Model: Development of shared datasets with DirectQuery on Amazon Redshift and import tables; DAX measures for utilization and capacity KPIs.
• Development: Data analysis, data transformation and visualization in Power BI; extension and migration of business applications to Power BI; AI-supported development in VS Code with GitHub Copilot.
• Test Automation: Automated testing of Power BI reports with Playwright; setup of the test environment in Docker containers.
• User Communication: Concept and implementation of a central information page with hot news, changelog and known bugs, access from reports with report filters, updates via Power Automate.
• Deployment: Management of Power BI Deployment Pipelines across the DEV, TEST and PROD environments.
• Agile Working: Work in an agile team according to SAFe (Scaled Agile Framework); refinement of user stories and features including effort estimates in Jira; version control with Git and GitLab.
• Quality & Documentation: Reviews for quality assurance, error analysis and resolution, technical documentation in AsciiDoc and Confluence.

Technologies: Power BI, DAX, Power Query, DirectQuery, Amazon Redshift, Git / GitLab, Deployment Pipelines, Playwright, Docker, AsciiDoc, Power Automate, Jira, Confluence, VS Code with GitHub Copilot, SAFe

Results:

• Capacity management KPIs from multiple source systems combined on one platform
• Transparency regarding current and future route utilization and construction activity across the network
• Easy access to analyses for users
• Automated regression testing of Power BI reports
• User communication implemented: central information page with hot news, changelog and known bugs, directly accessible from the reports

Design and implementation of a “unified-commerce” platform for SMEs to sell and deliver multi-product bundles

Achievements: Designed and delivered a fully functional, CPQ-based “buy flow” process for configuring and selling multi-product bundles on time, and secured customer approval within the specified 90-day timeframe. Successfully tested the integration of various interface services for customer search, customer data enrichment, address validation, service qualification, phone number validation, credit checks, appointment selection and quote-to-order transition.

Responsibilities:

• Strategic goal delivery: Translating strategic customer goals into action and delivering them (e.g. release content, business value).
• Backlog management: Creating and refining backlog items (Initiatives, Epics, User Stories, Defects) in close coordination with the project team and client.
• Prioritization & releases: Owning Product Backlog prioritization and delivery of defined release goals.
• Deliverable tracking: Tracking work completed by suppliers and the client.
• Roadmap & release planning: Developing and delivering roadmaps and release plans together with the client.
• Scope ownership: Owning the contractually agreed scope of work.
• Claim management: Proactive claim and change management with the client.
• Team coordination: Managing and coordinating the development team.
• Leveraging synergies: Using synergies between client projects and product development.
• Proposal preparation: Preparing proposals (with supervision) and presenting them in person to clients and partners.

Skills: Developing, communicating and delivering product visions; Product Backlog Management; Stakeholder Management; Regular reporting to management and steering committees; Requirements analysis & engineering; Planning and documenting workshops; Functional leadership and coordination of (distributed) project teams and external service providers; Epic Management; User Story specifications; Creating use cases, supporting software testing and User Acceptance Testing (UAT); Release Management and sprint planning; TO-BE process design; Process optimization; Planning, designing and specifying interfaces to existing and new systems; Identifying, assessing and managing project risks; Proactive claim and change management; Facilitating sprint planning and reviews; Data migration; Scrum; Kanban; REST API; JSON; XML; BPMN; UML; Jira; Confluence

• Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility

• Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture

• Pipeline orchestration with Azure Data Factory

• Improved and automated the development and deployment process by integrating Git and GitHub Actions

• Technical leadership of the Data Engineering team (3 employees)

• Led workshops to optimize and stabilize the data platform and development process

• Collected and prioritized new requests and maintained the product backlog

• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural