Data Quality Experts in Munich

• After several S/4 go-lives, structure, role clarity, and decision clarity were missing in Finance and IT; governance mechanisms, prioritization logic, and responsibilities were not defined well enough.

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

• The existing operating model between Finance, Controlling, and IT was not working, which affected transparency, collaboration, and decision paths.

• Designed the transformation and organization architecture for Finance and clarified roles, decision 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, steering routines, and cross-functional collaboration.

• Enabled leaders and teams, especially Global Process Owners, Key Users, and Finance Leads (systemic organizational development / leadership).

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

• Restored structural steering capability by clearly defining roles, decision paths, and priorities and anchoring them across the organization.

• Strengthened governance and cross-functional collaboration in a systemic way - Finance, Controlling, and IT worked again in consistent, aligned structures; friction losses dropped measurably.

• Harmonized working and communication logic, making coordination faster, more transparent, and less conflict-heavy.

• Enabled the organization in a sustainable way, including the build-up of a strong Key User / Process Owner community and clearly defined steering routines.

• Made the transformation structurally manageable - prioritized initiatives, clear risk and progress logic, and consistent decision formats increased execution speed.

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Developed & maintained customer analytical reporting solutions to identify revenue trends, performance drivers, risks & optimization opportunities to ensure data driven decision making across Sales, Finance, Product, Data Engineering & Controlling.
• Defined & analyzed customer trends & performance metrics to identify root causes behind variances, anomalies & emerging risks across business domains to deliver actionable recommendations.
• Developed & owned analytical data models & reporting layers to ensure scalability, performance & analytical robustness to support executive & operational reporting across business domains.
• Planned, tracked & executed projects by ensuring adherence to timelines, data accuracy, consistency, deliverables, reliability & data quality standards through rigorous validation & reconciliation processes.
• Raised the analytical maturity by formalizing analytical workflows, documenting data processes & standard operating procedures (SOPs) & conducting training sessions to drive adoption of self-service analytics & embed a data driven culture across operational and business teams.
• Took ownership of the end-to-end lifecycle roadmap from requirement gathering, collection, transformation, developing robust business logics to data storytelling & stakeholder delivery.
• Converted complexity into structured clarity by translating requirements & business processes into analytical recommendations to ensure alignment between non-technical & technical stakeholders.
• Conducted advanced SQL based analysis of complex business datasets to uncover trends, correlations & performance improvement opportunities.
• Drove process automation & efficiency improvements by leveraging Python, SQL optimization & AI assisted tools to reduce processing time & increase reliability across analytical & operational workflows.
• Standardized KPI definitions & reporting logic to ensure consistency & trust across reporting solutions.
• Developed process monitoring dashboards & analyses to identify inefficiencies, bottlenecks & compliance deviations across end-to-end business processes to derive actionable recommendations for process improvement & automation.

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

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment

DWH for customer and financial data

• Extension of the DWH with new data sources
• Report development
• Data quality management

Methodology: Scrum

Tools: Atlassian Confluence & Jira

Databases: Microsoft SQL Server

Programming languages: SQL, T-SQL

ETL: Microsoft SQL Server Integration Services (SSIS)

Frontend platform: PowerBI, Microsoft Reporting Services

• 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.

• Responsibility for daily HR operations across 4 studios in Germany, focusing on personnel administration and the employee lifecycle
• Drafting, reviewing, and managing all employment law documents (employment contracts, contract amendments, certificates, references)
• Preparing payroll, especially for hourly wage models, including data preparation and coordination
• Maintaining and managing timekeeping data in the system (Gfos) and ensuring data quality
• Proactively managing and tracking personnel-related deadlines (e.g., probation periods, fixed-term contracts, evaluations) in close coordination with studio managers
• Acting as the central point of contact and reminder for managers on all HR-related topics and processes
• Structuring and tracking HR processes while ensuring completeness and compliance of all documents
• Creating and maintaining HR documents, reports, and overviews in Word and Excel

• Design, development, and maintenance of end-to-end ETL pipelines for scalable and reliable data integration
• Support in data quality checks, testing, and migrations
• Development and maintenance of dbt models for structured, modular, and reusable data transformations
• Use of AI-driven development to improve ETL job creation and code quality.
• Development of CI/CD for automated deployment.

• Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
• Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
• Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
• Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
• Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
• Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
• Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
• Created and maintained dashboards in Power BI to provide actionable insights.

• Lead and develop a team of 3 employees across Talent Acquisition, Employer Branding, and HR Operations
• Manage an annual budget of approx. €95K and advise the Logistics Director on salary budget allocation for 400 employees (20% team growth in a year)
• Act as strategic sparring partner to management and leadership teams on people-related topics like talent development, organizational change, comp&ben and HR policies
• Set up all people processes around Talent Management, Employer Branding and Operations
• Support leadership on people development and talent management
• Implement & conduct training programmes (positive leadership, change management, intercultural communications)
• Drive cultural transformation initiatives in alignment with JYSK values and organizational goals
• Lead the annual HR strategy process, defining local priorities and setting measurable goals
• Lead the event team for the organization of employee events
• Drive change communications

• Group-wide responsibility for developing new business models, strategic support of corporate start-ups and managing equity in start-ups
• Direct management of 3 employees
• Direct reporting line to executive management
• Business Development: designing and building an information platform on the global machine base and customer sales/margins in the aftersales area based on SAP data, supporting sales planning as part of the budget, advising project teams on profitability calculations
• Digital Ventures: defining terms, developing processes to generate and develop new business models, operational validation of new business models to expand the group's business areas, strategic support of project teams in implementing new business models, cooperation project with Munich University of Applied Sciences, steering and supporting equity investments in start-ups

• 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.