Business Intelligence Experts in Vienna

Organizational Change Management for the strategic setup of a hybrid GBS rollout as part of a global, AI-driven Finance Transformation. End-to-end management of the OCM architecture in a highly complex on-, near-, and offshore partner setup [IN, PL, RO]. Successful completion of Phase 1 (Initial Strategy) and strategic pausing by the Executive Board after the early disclosure of critical vendor-side OPEX risks

• Systemic Baseline Assessment & Stakeholder Diagnostics: Evaluation of the global organization and analysis of the process landscape across 21 countries [AT, DE, CH, FR, UK, SI, RO, UA, RU, US, CD, CN, AR, MX, ZA, IN, JP] to precisely determine change requirements

• Architecting the OCM Strategy & Master Roadmap: Independent development of a comprehensive, AI-centered Change Roadmap for end-to-end management of all change initiatives across every project phase

• Data Quality & AI Agent Risk Mitigation: Auditing of Process Data Repositories (Celonis analysis); prevention of the ingestion of 58% synthetic training data to safeguard AI model reliability amid geopolitical supply chain tensions

• GBS Vendor BAFO Triage & Contractual Commitment: Critical review of Tier-1 vendor pitches and contractual commitment to a reduced Non-STP rate (from 7% to 4%) to avoid extreme manual rework with a planned FTE reduction (-63%)

• Executive Enablement & Board Alignment: Design of the GBS Transformation Executive Board Deck to strategically enable C-level executives and transparently present completely overlooked AI tokenization costs

• Targeted Change Communications & Engagement: Design and development of audience-specific communication measures to align the highly diverse, globally distributed stakeholder network

• Adoption Velocity & Resistance Measurement: Engineering of quantitative measurement tools (Pulse Check Survey) using Behavioral Dyads to identify resistance based on data and ensure sustainable success measurement

Results:

• Avoidance of disruptive misallocations: Stopping the ingestion of 58% synthetic AI-agent training data after discovering only 42% compatibility with existing processes, preventing critical GBS cascade errors
• Significant OPEX & effort reduction: Reduction of the Non-STP rate in Tier-1 vendor BAFOs from 7% to 4% alongside an impending 63% Finance-FTE reduction; avoidance of thousands of time-consuming manual correction processes
• 100% Delivery of the OCM architecture & ROI protection: Delivery of all OCM artifacts (Change Roadmap, Comms Plan, Executive Board Deck, Pulse Check Survey) and protection of ROI by identifying incalculable LLM runtime token costs

Independent practice serving clients in SAC-P and AI-enabled FP&A transformation, including financial model development for PE firm engagements, data cleansing with PowerQuery, workflow automation Claude Cowork, SAC-P scoping task-based assignments (Micro1.ai & Mercor.ai), and SAP partner network development.

• 2026 – Completed significant upgrade training for Positioning Business AI and SAP Cloud ALM Workshop (In-Person). Live Demos • SAC-P & Excel-Based Reports • Claude Partner • SAP Partner#: 1961209 (OE – Build)
• Fall 2026 – New effort to re-train/update past FI/CO, SAP BPC, SAP Platform to S/4 Finance & Core G/L Accounting
• 2026 – Upskilling for Transformation Toolchain. In-Person Workshops: Cloud ALM & SAP BTP • Joule Demo(s)
• 2025 – FP&A processes • Datasphere & Business Data Cloud • Team Workshops for AI • Toolchain & SAP Cloud ALM
• 2024 – Built key credentials on Deloitte S4 Experience • Group Reporting and SAC-P

• Analysis of existing work, information and decision-making processes.

• Identification and prioritization of suitable use cases for AI agents.

• Elicitation of functional and non-functional requirements.

• Design of collaboration between users and AI agents, including control and escalation mechanisms.

• Support for the implementation of the AI agents and adapted keyboard hardware.

• Business target vision for the AI-first transformation.

• Structured and prioritized requirements for implementation.

• Defined roles, interactions and control points between people and AI agents.

• Preparation for the gradual automation of productive work processes.

Techstack: AI agents, LLMs, agent orchestration, RAG, APIs, automation, hardware

Oracle PL/SQL, Oracle SQL, ITIL

• Support for the introduction of new digital exchange and communication structures as part of an organization-wide transformation project
• Conception, setup, and operational management of Viva Engage communities within the intranet as part of the rollout of new digital exchange and communication formats
• Planning and support of the pilot phase and the initial operational phase, including feedback and optimization loops
• Onboarding and enablement of employees and leaders in the use of new digital exchange formats
• Development of change management and activation measures to drive participation and adoption
• Moderation of discussions and creation of guidelines, FAQs, and netiquette
• Editorial and content strategy, including leadership communication
• Adaptation and implementation of central concepts and communication guidelines to organization-specific requirements
• Monitoring, reporting, and derivation of optimization measures
• Coordination with IT, data protection, communications, and business units

Refactoring and improving core APIs; implementing client change requests. Setting up metrics, traces, and logs monitoring infrastructure to support operations. Designing GitOps deployment and infrastructure as code. Applications and systems configuration in ArgoCD and Openshift. Confluence documentation of design, approach, and solution. Tech Stack: Java 8 & 21, Spring framework, JSP, JavaScript, Bash scripts, SQL, Grafana Stack, OpenTelemetry, Docker, DB2, Maven, Kubernetes Kompose.

Senior Expert / Program Manager

IT Services

• Management of internal projects for infrastructure modernization: setup and maintenance of test environments that realistically replicate complex customer networks.
• Resource coordination: planning server capacities and cloud resources for automated test runs.
• Implementation of CI/CD pipelines to integrate automated tests into the build process.
• Evaluation of performance bottlenecks through load testing (NeoLoad/JMeter) to ensure scalability.

Tools / Technologies: Jenkins, Docker, GIT, ButBucket, NeoLoad, Azure

SAP Business Data Cloud / Datasphere rollout

Technologies: SAP Datasphere | SAP BTP | SAP Analytics Cloud | ETL / ELT | Security & Governance

Tasks / Responsibilities:

• Designing and implementing data architectures in SAP Business Data Cloud / Datasphere
• Designing spaces, data products, and data flows for integrated data models
• Connecting SAP and non-SAP systems via SDI, ODP, APIs
• Integration with SAP Analytics Cloud for self-service analytics
• Building governance, security, and authorization concepts
• Creating architecture guidelines & performance optimization

Results / Achievements:

• Introduced a central data catalog & authorization concept
• Laid the foundation for self-service analytics

• Extraction, transformation, and cleansing of data from Microsoft Dynamics AX
• Creation of sales reports in Power BI
• Training employees in business intelligence
• Technologies: Power BI, SQL, SQL Server Integration Services (SSIS)

• Design and implementation of new functionalities in the areas of Lifecycle Management (LCM), Role Management (RLM) and Access Governance

• Adjustment of the company-wide Segregation of Duties (SoD) matrix to ensure regulatory and internal compliance requirements

• Further development and configuration of recertification processes

• Creation and adaptation of custom workflows, rules and tasks in SailPoint IdentityIQ (BeanShell, XML, Java)

• Use of static code analysis with SonarQube to ensure code quality and compliance with defined development standards

• Regular code reviews within the development team to ensure quality, share knowledge and follow clean code principles

• Work in an agile Scrum team with daily communication, sprint planning and reviews

• Coordination with testers, test managers and business departments to ensure quality and smooth production rollout

• Active involvement in release planning and deployment coordination, including test preparation, cutover activities and rollback strategies

• Analysis and sustainable resolution of issues in the IAM production environment (2nd- and 3rd-level support)

• Reproduction of complex errors, identification of root causes and implementation of lasting fixes

• Creation of technical analyses and recommendations for operations and further development

Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI

Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine

• Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
• Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
• Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
• Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
• Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
• Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
• Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).

• Project Lead, Sr. BI Expert, Data Scientist, Automation Engineer for Marketing Analytics | Customer Insights (retail, e-commerce)
• Product Manager: Asset Metadata Ingest & Provide
• Product Owner Business Intelligence – responsible for 2 teams: cloud data engineering, data warehouse (logistics)
• Product Owner for setting up a reporting platform on Azure & Power BI (finance)

Development of a visual concept for the digital representation of Medienhaus K&T Verlag