Data Warehouse Experts in Germany

• Task Engineering: Evaluating Coding Agents.
• Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
• Prompting & Translation: finding failure points where AI does not work, in German.
• Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
• Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
• Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
• Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.

• IT systems: Azure DevOps, SharePoint, Opal/Repost, JustinMind, Monday, SAP

• Analysis of requirements for branch software

• Coordination of intercultural teams

• Partly agile project organization

• Master data management / DMS

• UI/UX design and mockup creation

• Requirements documentation

• Digitalization of signatures

• Stakeholder management and workshop facilitation

• Billing/bank transfer

• Business analysis / requirements engineering

Concept and implementation of a unified-commerce platform for SMEs for selling and building multi-product bundles

Successes: On-time concept, delivery, and customer acceptance of a 100% functional, CPQ-based buy flow process for configuring and selling multi-product bundles within the given 90-day time frame. Successfully tested integration of various interface services for the following areas: customer search, customer data enrichment, address validation, service qualification, phone number validation, credit check, appointment selection, and quote-to-order transition.

Responsibilities:

• Strategic target delivery: deriving and implementing strategic customer goals (e.g. release content, business value).
• Backlog management: creating and refining backlog items (initiatives, epics, user stories, defects) in close coordination with the project team and customer.
• Prioritization & releases: responsibility for prioritizing the product backlog and delivering defined release goals.
• Deliverable tracking: tracking work results on both the supplier and customer side.
• Roadmap & release planning: developing and implementing roadmaps and release plans together with the customer.
• Scope responsibility: responsibility for the contractually agreed scope of services.
• Claim management: active claim and change management toward the customer.
• Team coordination: steering and coordinating the development team.
• Using synergies: making use of synergies between customer projects and product development.
• Offer preparation: preparing offers (with supervision) and presenting them on site to customers and partners.

Skills: development, communication, and implementation of product visions; product backlog management; stakeholder management; regular reporting to management and steering committees; requirements analysis & engineering; planning and documenting workshops; functional leadership and coordination of (distributed) project teams and external service providers; epic management; user story specifications; creating use cases, support with software tests and user acceptance testing (UAT); release management and sprint planning; design of target processes; process optimization; planning, concept, and specification of interfaces to existing and new systems; identification, assessment, and steering of project risks; active claim and change management; facilitation of sprint planning and reviews; data migration; Scrum; Kanban; REST API; JSON; XML; BPMN; UML; Jira; Confluence

• New connection of the product interfaces of the Financial Data Warehouse (FDW) directly to the Abacus 360 native interfaces
• IT environment: PC, client-server, Citrix remote client, Oracle DB
• Mapping of FDW outbound to Abacus 360 Native
• Analysis of requirements documents, business concepts, and existing interface rules
• Definition of new FDW rules for outbound to Abacus 360
• Adjustment of test scripts for the new interfaces
• Execution of tests to ensure correct data delivery and processing

I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.

I delivered following projects and engagements as a freelancer.

• Data Migration of CRM System for AL-FA Objekt Service Gmbh
• Microsoft Software Resales Partnership

I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer

Technical Focus Areas

• Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
• DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
• Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
• MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
• Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.

• Definition and setup of the subject areas
• Building a governance model for the department with the areas of responsibility
• IT strategy, project management, process management, and quality and sustainability management
• Developing a communication strategy within the group
• Creating the IT strategy
• Designing templates, guidelines, and processes for consistent work
• Capturing strategic guardrails and grouping ongoing projects – deriving a roadmap for strategic planning
• Reviewing ongoing projects
• Creating staffing calculations and volume structure
• Defining job profiles

• Technical leadership and further development of a team of 28 IT staff (internal & external) in the areas HelpDesk/HelpLine, RHEL (Red Hat), MUREX (trading system & applications), SAP basis operations
• Managing external service providers (including FI-TS for SAP basis operations)
• Personnel, resource and budget planning for the IT department and projects
• Introducing and establishing regular communication formats (weekly status meetings, team and cross-department meetings)
• Ensuring application operations in a hybrid environment (Windows/Linux with database and web/application servers)
• Supporting transformation projects to modernize the application landscape (e.g. DevOps approaches)
• Setting up and implementing a digital IT procurement for hardware & software (e.g. with DELL)
• Developing and managing the "IT Operations DOS" department based on corporate strategy
• Preparing management reports & decision papers on IT projects, optimization potential and automation opportunities
• Representing the department in the advisory boards of the Rentenbank and ensuring regulatory compliance (BaFin §44, GDPR, BSI, MaRisk)

Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.

Financial Data Integrity & ERP Governance

• Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
• Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
• Validated SAP reports, establishing baseline data quality standards for Finance team consumption
• Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs

Finance Reporting Transformation

• Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
• Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
• Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
• Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models

Power BI & Analytics Enablement

• Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
• Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
• Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team

Transformation Infrastructure & Collaboration

• Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
• Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
• Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization

Outcomes

• GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
• Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
• Power BI transformation roadmap presented and approved by Finance leadership
• Jira-based project governance live; Finance transformation now tracked with full sprint visibility

Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python

• 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.

Tools: Fabric, AWS, dbt, Power BI, SQL, DWH, R, Python

• Supported customers in implementing an architecture design for extracting and preparing data
• Planned the design and implementation of the BI and DWH platform
• Ensured the scalability and performance of the data platform

• Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
• Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
• Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
• Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.

• 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

Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present

• Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
• Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.

Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025

• Concept development and solution design for new end-to-end processes including technical interfaces
• Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
• Analysis and validation of data models
• Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
• Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
• Documentation and comments on technical and business requirements to support implementation in agile squads

Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present

• Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
• Development of business solution concepts for migration to the target system, including system integration and data flows
• Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
• Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
• Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.

Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.

Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows