SAP Analytics Cloud Experts in Munich

• IT Sourcing & Carve-out: RFP management for IT client hardware and services as part of the Rheinmetall carve-out.
• Contract Management: Drafting of MSAs and SOWs taking into account AVB, BVB and LSA as well as Service Delivery Contracts.
• Vendor Transition: Strategic transition management to replace legacy contracts and establish new supplier relationships.
• SaaS Procurement: Negotiation of SaaS license agreements based on TCO and cost-effectiveness analyses.
• KPI: On-time transition of all 12 global group contracts, achieving 18 % cost savings on the IT hardware basket and 20 % cost avoidance for SaaS licenses – measured against the critical carve-out project plan and achieved through structured transition management.

• Providing expertise in management consulting to support the improvement of frontier AI models for a leading AI lab

• 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.

AI Assistance and Target Vision for Partially Autonomous Energy Portfolio Management

Building an AI control layer directly on the up-to-date daily live portfolio of a large energy provider — not as an isolated pilot, but as an operational extension of the existing DB1 and portfolio management. The goal is the gradual development from assistance through monitoring/alerting to analysis agents with Human-in-the-Loop approvals, supplemented by a role-specific System of Engagement alongside the BI System of Record. At the same time, the business case, target vision and management pitch compared with static monthly reporting are being developed.

• AI control layer: Design and build on the existing live portfolio data product (several million contracts) — development stages assistance → monitoring/alerting → agents with Human-in-the-Loop approvals.
• LLM-supported data analysis: Semantic queries, SQL/tool integration and additional RAG components based on portfolio, plan-versus-actual and data quality data (Azure OpenAI, Snowflake), with drill-downs to individual contract level.
• Analysis agents: Multi-stage agents for variance and driver analyses of churn, price adjustments, volumes and procurement costs.
• Views concept: Role-specific interfaces for business units, management and C-level as a System of Engagement alongside the BI System of Record.
• Business case & pitch: Target vision and cost-benefit argumentation compared with static monthly reporting.
• LLM setup (privacy & security): Coordination with IT Security and Data Protection — EU region, data separation and approval processes.
• Agent architecture: Multi-stage agent pipelines (analysis → validation → summary) with documented data sources, tool calls, review steps and source references for each statement.
• Data foundation: Built on the up-to-date daily DB1 data product (Snowflake, dbt) — portfolio, plan-versus-actual and data quality metrics as the common basis for all AI analyses.
• Guardrails & evaluation: Evaluation and approval processes for LLM responses relating to management-relevant statements — test sets, metrics and human review.
• Prototyping & validation: Iterative validation of agent responses with the business unit — test question catalogue, feedback loops and response quality for each release.
• Roadmap & development stages: Detailed stages from assistance → monitoring/alerting → partially autonomous management, including transition criteria and governance for each stage.
• Integration: Integration into the existing BI and data landscape — BI remains the System of Record, while the AI layer provides interactive drill-down paths as the System of Engagement.
• Enablement: Enablement of business users — prompting guides, training and an operating model for ongoing use.
• Management: Coordination of business units, Data Engineering, IT Security and Data Protection.
• Change Management: Communication and expectation management with business units and management throughout the development stages.

Results:

• Built on an existing up-to-date daily data product with several million contracts
• Established an LLM setup coordinated with Data Protection and IT Security in the EU region, including data separation and approvals
• Defined three development stages through to partially autonomous management
• Designed role-specific views for business units, management and C-level
• Developed the business case and management pitch for the development stages
• Established an iterative response-quality validation process with the business unit
• Designed the operating model for assistance operations and initiated validation

Stack: Azure OpenAI, Azure AI Foundry, Snowflake, dbt, React, TypeScript, Entra ID, RAG, Agentic AI, analysis agents, Human-in-the-Loop, Prompt Engineering, LLM Evaluation, LLMOps, GDPR / EU region, Azure DevOps, Python, SQL, Change Management

• Creation of the profit center report and statistical metrics report
• Gathering and analysis of requirements regarding the forecast for revenue and costs
• Implementation of various time series analyses and optimization of forecasts
• SAP process knowledge, SQL, Python
• Python with various libraries for time series analysis and Machine Learning

Streamline – implementation of S/4 HANA Utilities in cooperation with Accenture

• Consulting and coaching of program management (OPL)

• Planning and support in executing all organizational and system technical activities to migrate from SAP IS-U to SAP S/4 HANA Utilities

• Communication and coordination with involved stakeholders and committees (core team, program management, steering committee)

• Project and process management

• Coaching of the stream leads in the main project

• Requirements management for interface connection of ancillary systems (non-SAP systems)

• Risk management

• Resource and capacity planning

• Consulting the existing migration, test, interface/ancillary system, and training teams

• Consulting on managing the SAP systems cut-over

• Planning and management including necessary post-migration activities (e.g., verification, documentation, adjustments)

• Team coaching & servant leadership: supporting one or more Scrum teams as coach, facilitator, and servant leader

• Promoting self-organization, personal responsibility, and continuous improvement

• Facilitation and continuous improvement of Scrum events (daily, planning, review, retrospective)

• Ensuring adherence to Scrum values, principles, and practices

• Identifying and actively managing impediments to ensure team productivity

• Working with product owners, agile coaches, and leaders to resolve structural hurdles

• Supporting agile scaling in frameworks such as SAFe, LeSS, or Nexus

• Co-designing agile transitions as part of MVV's digital strategy

• Building an agile mindset in the organization through training, workshops, and active role modeling of agile principles

• Collaborating with other Scrum Masters and agile coaches in the company-wide agile chapter

• IT systems: ERP: SAP IS-U, SAP S/4 HANA Utilities

• Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
• Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
• Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
• Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
• Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)

• Further development of BW applications for First Data GmbH
• Migration of 3.x data sources to 7.x
• Adaptation/redesign of existing ABAP coding to ABAP-OO
• Creation of new data flows in BW 7.5
• Support of daily operations
• Operation and monitoring of BW applications
• Authorizations
• Deletion concept for business partners in BW
• Data archiving concept
• Development of program for automatic creation of SD orders
• ABAP, ABAP-OO, BAPI
• SAP BW 7.x
• SAP ERP