Data Quality Experts

• Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
• Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
• Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
• Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
• Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
• Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
• AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
• Creation of a historical data layer as a basis for trend and time-series analyses
• AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
• Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
• Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
• Breaking down overall requirements into clearly defined work packages and tasks
• Definition, prioritization, and management of milestones throughout the entire project lifecycle

Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code

• Hands-on development of AI-native product prototypes with specialized AI agents for research, requirements, business logic, UX/flow design, test case generation and quality assurance.
• Structured use and orchestration of AI agents through clearly defined roles, inputs/outputs and handover points; breaking down complex product tasks into verifiable work packages and iterative prototyping cycles.
• Establishment of human-in-the-loop quality gates to validate AI-generated results for functional correctness, consistency, completeness and feasibility; targeted rework cycles in case of deviations.
• Development of a regulatory GenAI/rules prototype for CRD VI with a structured decision flow, web UI, rule-based validation and automated test cases; iteration of the business logic through to a pilot-ready POC.
• Design of an AI-to-Action banking prototype: AI intent → consent → bank/product logic → conversion including admin console; translating the product idea into MVP scope, role model, user flows and clickable prototypes.

• Developed a market entry strategy for the claims division of an insurance services provider.
• Analyzed and optimized existing claims processes.
• Defined management metrics and KPIs to improve performance and efficiency.
• Advised management on market positioning and process digitalization.
• Led an IT team of 13 employees as part of an interim vacancy cover.
• Ensured stable IT operations and managed external IT service providers.
• Led regulatory projects, particularly the implementation of the DORA regulation.
• Prepared and supported an IT security audit.
• Change management and conflict moderation in a challenging transformation environment (FI migration).

• Development of a digital audit application for inspections in medical facilities. The goal is to connect on-site data collection, voice recording, documentation and downstream processes in one end-to-end, AI-supported workflow.

• Design and development of a Flutter audit app with Claude Code for the structured execution and documentation of inspections.

• Processing of voice recordings captured in the app through automatic transcription and AI-supported creation of structured inspection reports, followed by an approval process

• Connecting various data sources such as email, Odoo 19, attendance records and Google Drive via n8n to automate billing and follow-up processes

• Automatic provision of required documents and email delivery through n8n-controlled workflows, including the use of LLMs for text creation

• Skills: Flutter, Claude Code, LLM Integration, n8n, Odoo 19, Google Drive, Process Automation

• Product Analytics, Mobile App Tracking & Tracking Governance (B2C Mobility App) – agile project management (Scrum/Kanban)
• Product Ownership for Product Analytics and Mobile App Tracking of the EnBW mobility+ app; gathering, prioritizing, and translating business requirements into actionable concepts and Azure DevOps user stories with acceptance criteria.
• Derivation of tracking requirements when introducing new app features (including Resilient Map), definition of tracking parameters (screens, events, custom definitions), and ensuring privacy-compliant tracking (Firebase, GA4, Adjust) based on the tracking concept.
• Design and adaptation of dashboards and funnel reporting for campaigns (GA4 validation, onboarding and order flow analyses, conversion funnels, charging start flow) to identify drop-off points and optimization potential.
• Management of the technical raw data export (Adjust to BigQuery) and connection to the data warehouse/data lakehouse, including data mapping; collaboration with international development teams, Data Engineering, Marketing/Sales, and Product Management.
• Establishment of standardized tracking architecture, naming conventions, and governance; analysis and expansion of tracking (new features and “blind spots”), test design, handover to testers, and quality assurance and approval before releases; documentation in Conceptboard.

• Designed and moderated a NIS2 preparation workshop for RAS Reinhardt Maschinenbau GmbH and its IT service provider Catuno GmbH. Together with executive management and IT leadership, the current status was assessed, an initial GAP analysis was conducted and areas for action were prioritized based on ISO 27001.
• Developed an ISO-27001-based regulatory framework (ISMS) for NIS2 compliance, including a structured current/target GAP analysis, targeted improvement of the security maturity level and preparation of the organization for NIS2 audit readiness.

The program supports the comprehensive realignment of the German Consumer Panel Services business. It combines a significant panel boost with the reprocessing of historical data and the integration of new receipt data. By significantly expanding and stabilizing the panel with the involvement of external partners, the aim is to improve the validity of the data base and create a reliable foundation for methodology, weighting and customer reporting. At the same time, historically grown processes for data delivery, OCR, matching, item QC, methodology and reporting are being harmonized, further developed technologically and reorganized. The goal is a scalable end-to-end landscape with higher data quality, clear responsibilities, reliable governance and sustainably manageable operational processes.

• Overall management of the restatement program, including the integrated roadmap as well as milestones, dependencies, risks and management decisions.
• Coordination of the panel boost and alignment of the required data deliveries, quality requirements and prerequisites for methodology, weighting and reporting.
• Alignment of business, product, data science, technology, operations and external partners around a shared target picture, aligned priorities and an integrated approach.
• Design of the organizational change triggered by the fundamental realignment of the data base, methodology and management logic, which has a lasting impact on established decision-making and collaboration patterns.
• Establishment and further development of governance, reporting and escalation structures as well as program-wide monitoring and operational processes for reliable management and sustainable handover.
• Management of critical data, technology and provider dependencies, including reprocessing, OCR transition and the timely synchronization of delivery, testing, methodology and reporting.
• Orchestration of international collaboration with teams and stakeholders in Germany, the United Kingdom, Portugal and Romania, as well as with external suppliers in Germany and Austria.

Impact Areas and Expertise: Program & Delivery Leadership, Business & Technology Alignment, Organization & Transformation, Governance & Sustainable Operations, Strategy & Target, Methodic Leadership, Transformation & Change Leadership, Executive Advisory

• Development of a production-ready Enterprise AI solution for the automated processing of invoices and business documents
• Integration of Azure AI Document Intelligence and LLM technologies into existing business processes
• Development of robust REST APIs for automated document processing and system integration
• Extraction, validation, and storage of structured invoice data in Azure SQL as a base for analytics and machine learning models
• Development of an AI-based recommendation engine with machine learning and deep learning to generate personalized product recommendations based on historical purchase data
• Implementation of logging, monitoring, error handling, and validation mechanisms for stable production use
• Collaboration with business teams to define business rules and integrate the solution into existing enterprise processes

Technologies: Python, Azure AI Document Intelligence, Azure OpenAI, Azure SQL Database, REST APIs, Machine Learning, Deep Learning, OCR, Pandas, JSON, Workflow Automation

• After several S/4 go-lives, Finance and IT lacked structure, clarity of roles and decisions; governance mechanisms, priority logic and responsibilities were not sufficiently defined.

• Unclear interfaces, high coordination effort and inconsistent ways of working led to organizational instability and limited leadership and management capability.

• The existing operating model between Finance, Controlling and IT was not functional, affecting transparency, collaboration and decision-making paths.

• Designed the transformation and organizational architecture for Finance and clarified roles, decision-making paths and priorities.

• Diagnosed and structured the Finance and IT organizations (DE/UK/PL), including collaboration, responsibilities and interfaces.

• Redesigned the Finance–IT Operating Model with a focus on governance, management routines and cross-functional collaboration.

• Enabled leaders and teams, especially Global Process Owners, Key Users and Finance Leads (systemic OD / Leadership).

• Managed the transformation portfolio, including clarity on risks, dependencies and cross-functional decision-making processes.

• Restored structural management capability by clearly defining and anchoring roles, decision-making paths and priorities throughout the organization.

• Systemically strengthened governance and cross-functional collaboration – Finance, Controlling and IT again worked in consistent, aligned structures; friction was measurably reduced.

• Harmonized working and communication processes, making coordination faster, more transparent and less conflict-prone.

• Established sustainable organizational capability, including by building a strong Key User / Process Owner community and clearly defined management routines.

• Made the transformation manageable in a structured way – prioritized initiatives, clear risk and progress logic as well as consistent decision-making formats increased execution speed.

I support the development of an industrial automation and communication product in which hardware, firmware, embedded software, system architecture, and testing work closely together. As a coach and technical sparring partner, I support product and project owners as well as development teams in turning product goals into a clear technical delivery structure.

• Technical Vision & Strategy: translated product goals into prioritized requirements, milestones, decisions, and executable work packages for HW-/SW teams.
• HW-/SW Collaboration: structured the interfaces between hardware, firmware, Embedded Linux/RTOS, fieldbus/connectivity, system test, and product management; made risks and dependencies transparent.
• Coaching & Leadership Sparring: clarified roles, responsibilities, prioritization, and decision paths with technical leads and teams and strengthened cross-disciplinary collaboration.

Methods & environment: Polarion, GitHub, requirements engineering, configuration management, PROFINET, embedded systems, agile delivery, coaching, and facilitation.

Time-limited interim assignment filling a vacant program leadership position: joint leadership of a complex software project and orchestration of several agile teams (business, development, and DevOps teams), as well as actively driving change processes.

• Program Management & Planning: Responsibility for creating and updating milestone, resource, and budget plans to ensure project objectives using agile and hybrid methods.
• Cross-functional Collaboration: Promoting cooperation and knowledge sharing across teams; resolving blockers through proactive conflict management and targeted facilitation.
• Stakeholder Management & Transparency: Ensuring transparent and audience-appropriate communication within and outside the project organization using modern project management tools.

• Relaunched a self-developed semantic name recommendation product by combining semantic search, graph-based similarity analysis, LLM-/RAG-supported content, and AI-assisted development processes.
• End-to-end responsibility across the product lifecycle—from use case definition and solution design through prototyping and evaluation to the iterative development of the roadmap.
• Evaluated AI use cases in terms of user value, technical feasibility, data quality, governance, and operating costs to guide MVP scope, roadmap decisions, and continuous product improvement.

• Redesign of legal operations: standardised workflows reducing routine effort by up to 80%, with source citation, hallucination check as quality gate, role model, logging and audit trail.
• Compliance-by-design operating model (EU AI Act readiness, GDPR, eIDAS) with documented, releasable process steps.
• Roadmap, sprint planning and release management for an agentic RAG platform with counsel-in-the-loop approval, audit trail and German hosting.
• EU AI Act readiness, GDPR and eIDAS requirements managed as first-class project deliverables; go-to-market for two customer verticals.

Lead Business Analyst – Analysis and optimization of private banking processes

• Responsibility for the business analysis and further development of business processes in private banking, with a focus on CRM, customer data management, and master data processes

• Carrying out a comprehensive business process analysis to identify optimization potential, business gaps, and improvement opportunities along the customer lifecycle

• Gathering, analyzing, and structuring business requirements in close cooperation with business units, management, IT architecture, and development teams

• Creating and aligning business concepts, process models, user stories, and requirement documentation as the basis for technical implementation

• Analyzing and optimizing existing master data processes with a focus on data quality, responsibilities, and efficient data maintenance

• Designing and further developing CRM customer data processes while taking regulatory requirements and business goals into account

• Planning and moderating workshops with business, IT, and stakeholders for requirements analysis, process design, and solution finding

• Managing requirements and ensuring consistent communication between business and IT

• Using AI-supported analysis tools to help with requirements analysis, structuring information, and improving documentation quality