Data Lake Experts

• Built a data integration platform for high-, medium- and low-voltage assets to enable contextual analysis of time series with master data from SCADA control systems (IEC 60870 104), INIS and SAP.
• Responsible for the architecture and implementation of the solution, and acted as a sparring partner for the Product Owner.
• Technologies used: Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter and various API gateways.

• Developed a market entry strategy for the claims division of an insurance services provider.
• Analyzed and optimized existing claims processes.
• Defined management metrics and KPIs to improve performance and efficiency.
• Advised management on market positioning and process digitalization.
• Led an IT team of 13 employees as part of an interim vacancy cover.
• Ensured stable IT operations and managed external IT service providers.
• Led regulatory projects, particularly the implementation of the DORA regulation.
• Prepared and supported an IT security audit.
• Change management and conflict moderation in a challenging transformation environment (FI migration).

• Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility

• Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture

• Pipeline orchestration with Azure Data Factory

• Improved and automated the development and deployment process by integrating Git and GitHub Actions

• Technical leadership of the Data Engineering team (3 employees)

• Led workshops to optimize and stabilize the data platform and development process

• Collected and prioritized new requests and maintained the product backlog

• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural

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.

• Implementation / restructuring of various digital payment use cases
• Project leadership and management, including scheduling, resource planning, and budgeting
• Implementation of posting processes in SAP in the subledgers and processing of account statements for invoice verification
• Definition of future operations and operating processes
• Collaboration with stakeholders to define business requirements and ensure that the project solutions meet them
• Identification and management of project risks and issues, including the development of risk mitigation and problem-solving strategies
• Promoting user acceptance through effective communication, training, and support strategies
• Advising on the practical implementation of various GDPR rulings in IT and business processes

• 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.

Multi-Agent Document-Generation Platform

Problem:

Turn a single prompt into a well-researched, structured and cited document, while keeping the user in control: every stage can be reviewed, corrected or revisited before the system moves on.

Architecture:

A multi-agent system orchestrated by a central controller. More than 20 specialised pydantic-ai subagents (understanding, structuring, planning, research, writing, assembly, cross-reference check, glossary, citation, reference table and more) pass results forward through a shared plan persisted in Postgres (asyncpg); a runner layer dispatches each task by name to its agent, and mechanical steps such as formatting, table of contents and list of figures are deterministic code instead of LLM calls. Provider (Anthropic or OpenAI) is a configuration setting, and responses stream over Server-Sent Events.

Hosting & Infrastructure:

Stateless container run as a Scaleway Serverless Container on a private network with managed PostgreSQL, object storage for finished documents and assets, and centralized log shipping (Loki / Scaleway Cockpit), provisioned with OpenTofu modules and deployed through GitLab CI; usage is metered per API key.

My Contribution & Key Decisions:

• Central decision controller: a satisfaction classifier turns the user's free-text feedback into a verdict (keep working, advance, cancel or revise an earlier task), and a middleware applies it to the plan. Plan progression supports jumping back to earlier tasks and re-running the stages after them.
• Research and writing fan-out: planning produces a plan from which a research-design agent generates individual research tasks and a writing-design agent generates individual writing tasks, each linked to the research it needs. Every task runs in its own dedicated agent with its own conversation history.
• Self-review and human-in-the-loop: after each step a critical-thinking agent reviews the output; the user can accept, refine, or ask questions about a critique before the plan advances.
• MCP integrations: two remote MCP servers, web search and internal document search, connected through pydantic-ai with retries and long-running tool-call timeouts. Classifier agents decide per task whether web search is needed, and a small model condenses raw search results into structured findings before they reach the writing agents.

Usage Metering:

Clients authenticate with an API key validated against a key-management service; consumption is charged in credits calculated from token usage per model plus a markup, and exhausted quota is answered with HTTP 429.

• Client — Podimo ApS (podcast & audiobook streaming): build the finance reporting layer on BigQuery + dbt + Airflow, including the core revenue-transaction fact tables used across finance reporting.
• API automation: design and build a BigQuery → Airflow → Microsoft Dynamics 365 Business Central REST-API pipeline to automate sales-invoice posting, with idempotency and master-data sync between systems.
• Delivery: sole engineer on the engagement — requirements, modelling, orchestration and stakeholder communication with the client finance team, end to end.

PMO & Project Organization Blueprint for Restructuring

Renewable Energy / Solar Equipment

Technologies / Methods: PMO setup, KPI tracking, project organization, Jira, Confluence

• Developed measures to improve management control during a restruct...

• Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
• Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
• Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
• Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
• Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
• Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
• Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka

Procure Ai builds a procurement platform with tools to optimise purchasing and supplier management, delivering real-time analytics, cost-saving insights, and automated workflows. A common data model integrates and enriches data from multiple ERP and e-procurement systems including Ivalua, SAP, Coupa, WPS, and Jaggaer.

06/2025 – TODAY:

• Architecting and building a new AI-native procurement platform with document intelligence, an agent orchestration layer using Mastra and LLM-based workflow automation across supplier, intake and category management use-cases
• Shipped agentic engineering workflows across the development team, enabling LLM-assisted code generation and review automation, measurably reducing cycle time on repetitive development tasks
• Migrating the Design System from Material UI to shadcn/ui with Tailwind, improving consistency and reducing frontend build overhead
• Staying hands-on across frontend, backend and AI features while the engineering team grew from 10 to 20+ engineers: hiring, onboarding, 1:1s and mentoring

06/2020 – 06/2025:

• Joining as the first engineer after the two founders; shaping platform architecture and product vision from scratch in close collaboration with the CTO, growing the platform to serve 10 enterprise customers
• Leading fullstack feature development on the core procurement platform, with focus on Analytics, Search, and Autonomous Negotiations use-cases: defining MVP scope, aligning technical decisions to customer outcomes, and cutting work that wasn't delivering value
• Challenged a field-based configuration request for Autonomous Negotiations and instead built a node-based rule builder matching how category managers think in conditions and branches; later reused across other workflow and decision configuration use-cases
• Designing and implementing multi-tenant authentication and fine-grained authorisation based on organisational units
• Architecting and building a multi-tenant Admin Application for managing customer installations across environments, covering configuration, feature flags, and i18n
• Creating and maintaining a custom Design System built on Material UI, used across the full product
• Setting up and maintaining CI/CD pipeline and full QA suite (linting, unit, integration, and e2e testing)
• Architecting and implementing a multi-environment release process using Helm and Helmfile; owning infrastructure as code across AWS and Azure
• Researching and piloting new tools and frameworks; making build-vs-buy decisions to balance velocity, cost, and long-term maintainability
• Grew the engineering team from 4 to 10+ engineers, mentoring engineers and building a culture of ownership, code review and iterative delivery

Technologies: TypeScript, JavaScript, React, Node.js, Fastify, GraphQL, GraphQL Codegen, GraphQL Mesh, GraphQL Yoga, Hasura, Apollo Client, REST, CubeJS, PostgreSQL, Prisma, Elasticsearch, Meilisearch, Typesense, Kafka, Avro, Karapace, Kubernetes, Docker, Terraform, OpenTofu, Helm, Helmfile, GitLab CI, Keycloak, Better-Auth, OpenFGA, Nx, Vite, Vitest, Playwright, Testing Library, Storybook, Chromatic, Material UI, shadcn/ui, Tailwind, React Flow, recharts, i18next, Backstage, Grafana, Sentry, Zod, Claude Code, Codex, Mastra, Vercel AI SDK, Vercel AI Elements, AWS, Azure

• Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)

• 5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models

• Proposal and feasibility assessments for BI and reporting projects

• Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development

• Custom ERP system

• Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.

• Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.

• Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.

• Timesheet app

• Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.

• Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.

• Cash-flow modelling

• Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.

• Implementation: Built and extended the CF model to include project-development cash flows.

• Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.

• Defined and established the areas of responsibility
• Built a governance model for the department and its areas of responsibility
• IT strategy, project management, process management, and quality and sustainability management
• Developed a communications strategy for the group
• Created the IT strategy
• Designed templates, guidelines, and processes for consistent ways of working
• Recorded strategic guidelines and grouped ongoing projects – derived a roadmap for strategic planning
• Reviewed ongoing projects
• Prepared staffing calculations and capacity planning
• Defined job profiles

• Lakehouse build: Designed and built the member & eligibility domain of an Azure Databricks healthcare lakehouse, ingesting SQL Server, file and REST/SFTP sources (JSON, CSV, XML, Parquet) via Azure Data Factory into ADLS Gen2.
• Medallion pipelines: Transformed data through bronze, silver and gold Delta Lake layers with PySpark and Spark SQL; used Delta Live Tables / Lakeflow with built-in expectations for declarative, quality-checked pipelines.
• Platform modernisation: Delivered a SQL Server-to-cloud platform: ADF → ADLS Gen2 → Databricks → dbt Core models → Snowflake → Power BI, replacing legacy reporting with governed analytics.
• Robust ETL: Built metadata-driven, idempotent full, incremental and watermark-driven loads with schema evolution and failure-state handling, improving reliability and re-runnability.
• Data modelling: Designed Kimball star schemas with SCD Type 1 & 2 dimensions; tuned slow queries and pipelines using execution plans.
• Governance & security: Applied Unity Catalog RBAC, lineage and audit logging, with Azure Key Vault secrets and managed identities, to meet HIPAA and GDPR requirements.
• Leadership & mentoring: Led a 6-person team (2 data engineers, 2 analysts, BI developer, QA); mentored engineers, set delivery standards and coordinated with international stakeholders.
• Delivery & AI-assisted work: Ran CI/CD and work tracking in Azure DevOps; built Power BI semantic models with DAX and RLS; used Genie Code, Claude and Copilot to accelerate PySpark/SQL development, DAX and documentation.