ETL Experts in Frankfurt

• Industry: Insurance, Trade, IT
• Customers & Projects: Consulting and selling insurance and similar services
• Main tasks: Insurance consulting (health insurance, retirement planning, wealth building); commercial services, inside and field sales; sales data analysis and forecasting; customer consulting and support; opening a new sales headquarters for private and business customers; business development & innovation management; business use case development; process optimization; stakeholder management; team leadership and training; preparation and delivery of trainings;
• Technologies used: Microsoft Office 365, Microsoft Teams, Jira, Draw.IO, Camunda 8, Java (8, 17,21,25), Git, Spring Boot, Spring Batch, Spring Data REST, Spring Web, Spring Security, J-Unit, Playwright, Lombock, Vaadin, H2, PostgreSQL (16, 17 18), pgAdmin, Docker, LLMs, JasperSoft Studio, JasperReports

• Supporting the International Web Presence of the BA (IntWeb) project in the area of quality management, with the aim of taking responsibility for the quality of processes and project results while considering BA standards. The main objectives of the project are to give professionals abroad a quick overview of their opportunities for moving to Germany and to enable them to take the necessary steps consistently and with digital support by providing access to services.

• Defining the general guidelines in the QA handbook

• Summarising test results in QA reports for PLA

• Analysing project results for improvement opportunities

• Quality management of requirements analysis (particularly processes, methods, and tools)

• Ensuring compliance with SERA requirements

• Creating a cross-project test concept

• Agreeing on sprint completion reports

• Formal review of work results in accordance with requirements and/or the project plan

• Contact person for internal audit, external audits by auditors, or BRH (Federal Court of Audit)

• Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

• Built an MCP (Model Context Protocol) layer for Mwanachama's agency service, turning domain manager methods into callable AI-agent tools. This included a composite tool that builds a full organization design (org chart, goals, workflows, RACI matrix) from one specification.
• Built the chat-driven agency builder (Wakala Studio and API), where an organization describes its structure in natural language and an AI agent uses those tools to construct and modify the live design.
• Added an insights service so an organization can review AI-agent interactions and completed work. Insights from that review feed back into solution design, gated by architect and user sign-off.
• Alongside this, designed and built the platform itself: ~20 Go microservices on PostgreSQL, Flutter and React clients, deployed on Kubernetes.
• AI agents scan the platform autonomously for security gaps and run scripted tests, covering API (Postman-style) and UI testing. The rest of the work stays supervised. No rogue agents, promise.
• Building an AI-native enterprise platform that structures organizational data, workflows and responsibilities for both people and AI agents.
• Models accountability through RACI, allowing human and AI participants to take different operational roles, including Responsible, Accountable, Consulted and Informed. AI agents can also take controlled approval roles where the organization assigns that responsibility.
• Extended the organizational and operational-risk themes from my Executive MBA thesis into software, making roles, processes and controls explicit and machine-readable.
• Structures enterprise context so LLM interactions use more relevant information instead of repeatedly processing large amounts of unstructured content.

Independently built a data platform with cross-system process monitoring.

• Designed the Bronze/Silver/Gold architecture and Python-based pipelines for diverse operational sources.
• Cleaned, harmonized, and validated data; processed and stored it in Parquet format.
• Tracked data history and built business-focused fact and dimension models for traceable reporting.
• Automated data delivery with Python and Power Automate (desktop and cloud); used SharePoint for archiving and data access.
• Developed the Power BI solution from data preparation through to visualizing process statuses, work progress, and deviations.

Technologies: Python, SQL, Parquet, Power BI, Power Query, Power Automate, SharePoint, Copilot

• Analysis of the existing reporting platform, including processes and governance topics, with stakeholders from Sales and Marketing.

• Detailed analysis and evaluation of customer-defined requirements for existing reporting and new dashboards to be established.

• Support for stakeholders in managing sales processes and identifying KPI trends at an early stage.

• Use of Microsoft Power BI as the central analysis and reporting platform.

• Development of a proposal for the required further development of processes and the Power BI platform.

• Documentation of AS-IS business processes and derivation of company-wide KPIs, including coordination with stakeholders.

• Analysis and assessment of the customer's Power BI platform.

• Analysis of processes and data governance.

• Documentation of AS-IS business processes.

• Development of recommendations for further developing processes and the reporting platform.

• Design and implementation of dashboards in Power BI.

• Development of company-wide KPIs and coordination with stakeholders.

• Microsoft Power BI.

• Data analytics.

• KPI definition and reporting.

• Dashboard design and data visualization.

• Stakeholder management and requirements management.

Statistical Forecasting Algorithm

• Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
• Migration from R/On-premise to Python/Snowflake
• Productionalization on Snowflake in cooperation with data engineers & DevOps

Monitoring Dashboard

• Data engineering for preparation & provisioning of necessary data/resources on Snowflake
• Development & deployment of a Streamlit dashboard in Snowflake

ML-based Probabilistic Forecasting on Vertex AI

• Development of a ML-based probabilistic forecasting algorithm from scratch
• Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI

Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow

• Responsible for the end-to-end application and integration architecture for the S-Bahn Hamburg maintenance digitalisation program. A highlight is the introduction of robots and permanently installed camera gates to automate vehicle inspections, allowing AI image algorithms to assess the condition of trains during operation.
• Deutsche Bahn has one of the largest SAP PM implementations in the world, which is a central component of this digitalisation.

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.

• Analyze business situation: stagnation of sales, small recurring customer rate, huge number of visitors but little conversion rate, average order value does not increase, no customer segmentation or targeting, performance marketing approach fails to acquire the right customer
• Advise on sales and marketing strategies and improve operations; agile coach advice with key business strategy using Scrum and Kanban
• Acquire key requirements and derive user stories for e-shop product owner development and customer data analysis
• Develop comprehensive 360 degree customer data model using Shopify and Amazon; implement data feeds from more than 10 systems (Klaviyo, Typeform)
• Develop meaningful ad-hoc data analysis detailing aspects of Triple Whale customer behavior using standard e-commerce KPIs such as AOV, Google Analytics, churn, conversion and abandoned checkout rates, ROAS, CPA, CPC; tools: SQL, Power Query
• Derive clear and data-driven customer segmentation and targeting; ETL processes and Power BI
• Introduce and feed new content agency with customer insights using GraphQL and Postman; improve messages, frequency, and targeted audience; Microsoft Planner
• Provide crystal clear data proof to steer new performance marketing approach
• Develop standard business operations reporting

• Led design, development, and deployment of data solutions supporting a major pharma acquisition for Takeda Pharmaceutical Company, delivering transparency reporting systems across Azure,Databricks (Python and Shell Scripting) platforms.
• Owned,Designed and developed scalable ELT pipelines to process Customer and Product data using Azure, complex SQL, Databricks, and shell scripting, enabling efficient data integration and processing across multiple sources including job orchestration and workflow automation.
• Implemented performance optimization techniques (query tuning, parallelism, workload optimization), improving system efficiency and processing time.
• Applied strong analytical and problem-solving skills to assess technical solutions and support business requirements for compliance and transparency reporting.
• Designed scalable data foundations suitable for downstream analytics and AI workloads.
• Led data quality initiatives by assessing multiple source data, defining quality metrics, and establishing processes for monitoring and continuous improvement.

• Presentation introducing generic A.I. and Large Language Models
• Explanation of legal frameworks (EU AI Act, US CLOUD Act, DSGVO)
• Systematic review of AI tools along the SDLC and holistic systems
• Comparison of on-prem LLMs vs. cloud-based solutions, as well as change management and works council considerations
• Moderation of the discussion and definition of next steps for introducing AI development tools

• Development and implementation of backend components with PL/SQL and Oracle Forms 12c. Adaptation and further development of the policy administration system. Technical consulting in UI design with a focus on integrating existing Oracle Forms and the requirements of the BIPRO framework.
• The project takes place in the technical environment of BIPRO, SQL databases and Oracle Forms applications. The assigned work includes backend development and technical further development in the above project with the following tasks:
• Development and implementation of backend components with PL/SQL and Oracle Forms 12c to technically map the business processes and ensure a stable and efficient system architecture
• Adaptation and further development of the policy administration system to ensure system functionality in line with the requirements of the new broker communication program
• Analysis of the existing system to identify and avoid errors and technical problems during implementation, in order to enable a smooth transition to the new system
• Carrying out patching and further development of existing Oracle and Oracle Forms applications to ensure compatibility and security of the systems in use
• Technical consulting in UI design with a focus on integrating existing Oracle Forms and the requirements of the BIPRO framework.

Label: PL/SQL, Java, Oracle RDBMS and Oracle Forms

• Built an API to ingest, clean, translate, and index EU tenders documents in Neo4j, enabling hybrid search with RAG and Cypher queries via a Streamlit dashboard
• Deployed the API on AWS Lightsail container services with CI/CD automation via GitHub Actions, ensuring stability through pytest unit and integration tests
• Designed and developed a comprehensive online course on data analysis using ChatGPT for professionals and learners, creating instructional videos and interactive Jupyter notebooks
• Utilized OBS and professional audio equipment to ensure high-quality video and audio content
• Led a CRM data normalization and cleaning project visualized via a Sankey diagram to aid customer understanding and pipeline development
• Implemented and validated a genAI-driven web crawling strategy on AWS, ensuring data quality, scalability, and CRM data augmentation