Data Migration Experts in Munich

Refinement of epics and user stories to achieve a higher degree of automation in CRM usage. Testing of new Discountsystem

• Delivered backend systems, data processing solutions, and software integrations for enterprise business applications.
• Designed and implemented API-based services connecting internal platforms with external systems.
• Built automated processing workflows to handle large-scale structured business data.
• Improved application performance by 30–50% through database optimization, caching strategies, and backend refactoring.
• Reduced manual operational effort by 40–60% by automating repetitive workflows.
• Supported production environments through troubleshooting, monitoring improvements, and continuous optimization.
• Authored technical documentation and led knowledge-transfer sessions to support long-term maintainability.

• Designed, developed, and configured scalable data applications aligned with business processes and technical requirements.
• Architected scalable, cost-effective data architectures leveraging Snowflake across AWS, Azure and GCP, integrating dbt for data transformation and modeling.
• Built and maintained robust ETL Data Pipelines, ensuring high data quality for seamless migration and cross-system integration.
• Demonstrated strong expertise in SQL & Python with extensive experience in data modeling, ETL/ELT pipeline development, and streaming data processing; proficient in Git-based version control, CI/CD practices, and testing frameworks, with solid knowledge of data quality, observability, cost optimization, security, and data governance principles.
• Led multiple data migration initiatives from SAP HANA to Snowflake using a modular dbt framework.
• Designed and maintained end-to-end data transformation workflows using dbt on Snowflake, implemented layered data models, optimized performance, and ensured high-quality data delivery for business intelligence and reporting.
• Managed development, QA, and production deployments through structured version control and release management using GitLab.
• Integrated and centralized data from multiple sources including relational databases, flat files, Excel, and large-scale systems into Snowflake.
• Applied strong expertise in Sales, Marketing, HR, and ERP data domains, developing and maintaining relevant KPIs and reporting solutions.
• Collaborated with cross-functional teams to deliver end-to-end data solutions on schedule through proactive issue resolution and effective coordination.
• Administered the Snowflake sandbox environment for Data Engineering division.
• Trained colleagues transitioning into data roles on Snowflake and provided technical guidance and mentorship to junior team members.

• Set up GUI test framework for testers and developers to easily create GUI tests
• Implemented automated GUI tests with QF-Test for stock trading software and PDF file comparisons
• Created comparison runs between different versions

Used technologies: QF-Test, Java, Jython

End Customer: Openry GmbH

E-commerce platform to globally commercialize high-quality Italian artistic productions. Several European shops are already operational and Asian markets soon coming up. My role as Agile Project Manager is to lead the complete team on both the customer and technical side (offshore) including strong strategic consulting, in a continuous delivery approach. As project in a small enterprise, the budget management aspects are particularly challenging, in a quest to deliver the maximum business value with minimal overheads. Technologies: Magento 2, M2E Pro, Linux, Apache, MySql, PHP (LAMP), Stripe

• Support for implementing the Pimcore CMS, support assistance, and partner management for the existing application landscape.
• Know-how transfer to the existing application landscape.
• Advising stakeholders on the new implementation.
• Support in data modeling for Pimcore.
• Designing and overseeing data migrations from Salesforce to Pimcore using ESB.
• Creating user stories.
• 3rd level support for business-critical processes.
• Technologies: Salesforce Marketing, Sales, and Service Cloud; Talend ESB; Pimcore; Shopware; ERP system Move; DB2; MySQL; MS Office; MS Visio; Jira; Confluence.

Introduction: Companies today face two major challenges: maintaining a pristine Workday tenant AND simultaneously developing an AI strategy that goes beyond mere experimentation. With CloudMcFly, I combine 10+ years of experience as a Workday Architect & PMP with cutting-edge AI strategy consulting. I don't offer theoretical concepts; I deliver implementable solutions. Core Services:

• 1. AI Readiness & Process Audit Not every process requires AI. I analyze your HR/Finance processes (Workday & Non-Workday) to identify "low-hanging fruits" for automation and AI integration. Outcome: A concrete action plan including ROI calculation.
• ️ 2. AI Strategy & Governance Roadmap From vision to execution. Together, we define guidelines (Ethics, Data Privacy, EU AI Act) and select the right tools (ChatGPT Enterprise, Copilot, Custom Agents). Outcome: A secure roadmap approved by Management and IT.
• ️ 3. Workday Architecture & Optimization As a certified Architect, I ensure your Workday tenant remains stable while we integrate new technologies (Launch, PEX, Delivery Assurance).
• 4. Enablement & Workshops An "AI Driving License" for your teams. Hands-on workshops on Prompt Engineering, Automation (n8n/Make), and operational efficiency.
• Interested in Pricing & Packages? Visit [link] The AI chatbot on my homepage knows all my consulting packages and can provide immediate details on pricing and availability. Give it a try!

• Responsible for cutover planning and go-live management of multiple parallel IT releases in the e-commerce environment
• Creating and maintaining cutover plans, runbooks and rollback scenarios, plus audit-ready documentation of all cutover activities
• Defining and managing go/no-go decisions, escalation paths and resource availability in the cutover window
• Coordinating technical and business workstreams, managing external service providers and ensuring data consistency
• Managing and reviewing trial cutovers, structured handover to the hypercare phase
• Cutover reporting and communication before, during and after go-live at decision-maker and C-level
• Result: All releases delivered on schedule, cutover processes sustainably established and handed over

• Designed and developed the "Credit Risk Engine" using Camunda, Node.js and Typescript
• Greenfield project for credit card credit assessment for existing and new customers, including EBA KPIs, SCHUFA and CRIF scorings
• Built and modeled workflows (BPMN) and decision logic (DMN) with Camunda Modeler in close collaboration with stakeholders
• Implemented service tasks, user tasks and jobs with Nest.js, Node.js and Typescript, including exception handling
• Backend-for-Frontend (BFF), frontend with React, Tailwind and Ant Design UI library
• CI/CD with GitLab, Kubernetes/Rancher

• Business intelligence and KPI specification and playbook for 35 European companies.

• Support of BASF units in change management for the introduction of a Sales & Operations Planning process based on OMP SOP

• Overall process definition, planning, training, tools, effective execution, and progress and quality measurement of test activities at the release level
• Defining and improving the test process
• Scheduling of releases
• Coordinating alignment with release management for test setup and data provisioning
• Coordinating migration test planning for Westnetz, Mitnetz, and EON Grid
• Monitoring test progress, audit-proof documentation, progress tracking via defects, OSS reports, and incidents
• Designing and coordinating potential test automation

IT environment: Jira Zephyr, Confluence, SIGMA, PowerBI

• Topics: Business Analysis, Data Privacy, Data Management, Stakeholder Management, Conceptualization
• This project focuses on developing and implementing a strategic approach for data deletion in SAP systems. The goal is to identify the relevant data and structures during system migration to ensure both data privacy and IT system efficiency. At the same time, downtime should be minimized and regulatory requirements met.
• Development of a comprehensive approach for data deletion in SAP systems, considering data privacy and business requirements.
• Ensuring efficient and structured data transfer to the new system.
• Optimizing system efficiency and reducing downtimes during migration.
• Creating functional and technical concepts to ensure compliant and sustainable data management.
• Topic preparation: Detailed study of the "data deletion" area to lay the foundation for a structured data migration.
• Definition of project structure: Setting roles, interfaces and the project's organizational structure.
• Regulatory requirements: Analysis of data privacy regulations and business requirements to define deletion criteria.
• Approach: Developing possible scenarios and methods for data cleansing and deletion.
• Deletion concepts: Creating functional and technical deletion concepts that structure the implementation and provide clear guidelines.
• Setting deletion criteria: Defining which data and structures to delete or transfer.
• Responsibilities: Clarifying responsibilities within the project team and among stakeholders.
• Analysis of ongoing activities: Identifying and collecting existing activities in the "data deletion" area.
• Effort, cost and timeline planning: Creating estimates for resources, effort and budget.
• Implementation initiatives: Developing and executing concrete measures to apply the defined deletion strategies.
• IT system efficiency: Analyzing the existing IT infrastructure to identify optimization potential for data deletion and transfer.
• Technology trends: Evaluating new technologies and tools that can support the data cleansing process.
• Cost-benefit analysis: Assessing the financial impact of data cleansing and the introduction of new solution approaches.
• Risk management: Identifying potential risks during implementation and developing appropriate mitigation measures.
• This project lays the foundation for a sustainable and compliant data transfer to a new SAP system. With a clear approach to data deletion, it meets data privacy requirements, reduces downtimes and increases the efficiency of the new system. The results and recommendations will help companies develop a future-proof data strategy that meets legal and business needs.

• Designed and evaluated high-quality prompts and completions for Large Language Models (LLMs), focusing on improving response accuracy, instruction-following behavior, and factual consistency.
• Annotated and rated LLM-generated outputs for grammar, coherence, relevance, and truthfulness.
• Developed RLHF-style preference data by ranking model completions to inform reinforcement learning fine-tuning cycles.
• Participated in prompt engineering experiments to assess the effect of instruction format, verbosity, and phrasing on model behavior.
• Conducted error analysis and quality assurance on large-scale NLP datasets, identifying edge cases and linguistic ambiguity affecting LLM performance.