Traceability Experts in Berlin

• Architected an enterprise Fabric-based data-product governance framework, authoring data contracts and schema-validation KPIs to enforce completeness, freshness and SLA standards across reporting data products.
• Operationalized pipeline observability by integrating Dagster orchestration data into automated data-health reporting, proactively validating data integrity and pipeline reliability before production reporting layers refresh.
• Established BI-as-Code and end-to-end governance through Git-based version control, CI/CD and Alpha→GA release management, strengthening lineage, schema-drift detection and production change traceability.

• Building up the Enterprise Architecture department. Preparing the convergence of IT / OT.
• Mapping the global business application landscape (6 countries).
• Concept for a graph model of the application landscape. Storing the results in the open-source graph database Neo4J. Various reports in the database query language CYPHER and the visualization component BLOOM. Automatic generation of IT architecture diagrams.
• Development of an application taxonomy to identify redundant applications.
• Applying Gartner's Software Portfolio Management TIME model (Tolerate, Invest, Migrate, and Eliminate) for portfolio management.
• Enterprise Architecture Governance: establishing architecture guidelines for documenting measures and decisions.
• Process modeling according to Porter (Value Chain).
• Various architecture approvals for change requests and documentation in Architecture Decision Records (ADR).
• Working on the RACI matrix for various processes.
• Working on business capabilities as preparation for a LeanIX rollout.
• Contributing to the concept for IT/OT convergence.
• Establishing architecture guidelines in a very pragmatic corporate culture. Knowledge about applications and responsibilities is spread across the world.

• Own the 12–18 month roadmap and key outcomes for Elli's enterprise customer platform, covering onboarding, pricing, billing, analytics and broader platform modernization; redesigned the Fleet onboarding funnel to double conversion, supporting a projected €20.7M revenue uplift by 2028.
• Lead the broader Energy Intelligence product and directly own its AI/ML, asset and portfolio-optimization capabilities, including MLOps and safe strategy deployment, strategy lifecycle management and backtesting; delegated data and V2G integration roadmap ownership to a new PO as the platform scope expanded.
• Built a Human-in-the-loop GenAI/RAG support workflow, increasing L1 resolution by 24%, routing accuracy to 91%, and reducing L2 workload by 30%.
• Introduced standardized data contracts and a self-service Python toolkit for traders and Data Scientists, increasing platform adoption by 15% and reducing support effort by 50%.
• Built and scaled a real-time orchestration product from 32 to 3,000+ endpoints across four markets, growing recurring revenue from €1.4k to €56.3k MRR.
• Developed product and AI capability across the organization, training 20 PMs on RAG, agents and prototyping; mentoring a junior PM and coaching an Enterprise Platform Tech Lead toward Product Management ownership.

• Used OpenCode and AI-assisted software engineering to design, implement, refactor, test, and document an end-to-end RAW/SDTM/ADaM pipeline in R for Dr. Falk Pharma (07/2026), including metadata-driven transformations, automated validation rules and QC, traceability, and reproducible clinical outputs.

• Led the end-to-end delivery of enterprise full-stack web applications by driving requirement analysis, solution design, frontend and backend development, database design, API integration, code reviews, team coordination, Agile execution, CI/CD deployments, production support, performance optimization, security implementation, and stakeholder collaboration to deliver scalable, high-quality software solutions.

• Converts natural language into JQL using RAG and pgvector. Returns structured JSON with a query, chart spec, and plain-text answer. A two-stage router answers general questions without touching the JQL pipeline at all.
• Interchangeable LLM backends: Ollama, vLLM, Groq, Anthropic Claude, AWS Bedrock - switchable at runtime, no code changes. Self-healing JQL: on Jira validation failure, feeds error back to LLM, retries up to 4 times. OCI Vault for secrets. Deployed on Oracle Cloud A1 with GPU inference over Tailscale private network. Open source.

Responsibilities: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.

Activities:

• Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
• Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
• Developed automated data pipelines with Python, dbt, and GCP services for various data sources
• Built monitoring and alerting systems for real-time platform monitoring
• Implemented data versioning and quality checks at every layer
• Designed automated testing and deployment pipelines in GitLab and Bitbucket

Achievements:

• Doubled production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
• Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, reducing configuration errors to 0
• Delivered a complete end-to-end data platform at ~10 €/month in infrastructure costs
• Migrated 7 database tables with 0 downstream issues
• Removed 100 % of exposed credentials, eliminating dependency on external vendors
• Delivered 3-team integration in 1 sprint

• Spearheading investor outreach and partnership development as founding MD, building the business case and technical narrative needed to attract initial funding and strategic collaborators in the digital health space
• Designing multi-agent AI systems for autonomous biosignal analysis, orchestrating LLM-based reasoning pipelines with domain-specific medical context to enable intelligent, clinical decision support

• Responsible for cross-department requirements management in collaboration with business units, IT, and external vendors
• Gathering, structuring, consolidating, and prioritizing business requirements from various company departments
• Modeling and documenting business processes using BPMN as a basis for transparency and further development of existing solutions
• Analyzing existing business processes and identifying optimization opportunities
• Refining business requirements with regard to feasibility, cost-effectiveness, and impact on adjacent processes
• Facilitating business alignment sessions with relevant stakeholders to refine requirements and support decision-making
• Creating actionable business concepts for IT development
• Supporting implementation, testing, and rollout of new or adjusted solutions
• Assisting in standardizing requirements and processes to build a reliable decision-making foundation

• Reimagine digital publishing by building a next-generation CMS ecosystem for our portfolio of web magazines, powered by an intelligent AI companion that augments journalistic creativity and decision-making. From real-time trend discovery and data-driven topic ideation to research, writing, refinement, and seamless publishing, the platform will transform how stories are created—enabling faster, smarter, and more impactful journalism while preserving editorial voice, integrity, and human oversight.
• Successfully launched the first two brands on the new CMS platform, establishing a scalable foundation
• Prepared three additional brands for migration and launch, aligning design, SEO, and technical requirements
• Established a unified CMS and AI-supported editorial workflow across multiple digital publications
• Enhanced journalist productivity and focus by automating repetitive tasks and supporting creative processes
• Improved speed, consistency, and quality of content delivery across the portfolio

• Vram.run: Rust, TypeScript, HF Inference API with 19 providers, 220+ HW configs, and 30+ cloud GPUs. Search a model to see which API providers serve it, which GPUs can run it locally (and how fast), and what cloud rental would cost. Or search your hardware and see what fits. Also includes a Rust CLI.
• Psychotron: JavaScript, Web Audio API, AudioWorklet, Canvas 2D. Front-end for flash fiction audiobook with Web Audio DSP chain featuring pitch-shifting, 12-voice chorus, flanger, 13-band EQ, and convolver reverb. Includes a 2D canvas effect morphing engine and synchronized teleprompter.
• RecentWork: Swift, macOS, FSEvents, launchd. macOS daemon that watches project directories and maintains a flat folder of symlinks to recently modified files. Homebrew installable.
• Mini-llm: Bash, macOS, launchd, Ollama, llama.cpp, MLX, Open WebUI. Single command that turns a Mac Mini into a headless AI server.
• ThatSlop: JavaScript. Chrome/Firefox extension for AI content detection on LinkedIn and Twitter.
• Smux: Bash, tmux. Human-friendly tmux wrapper that is Homebrew installable.
• Learn Rust Course: Rust. Course on Rust’s memory model for C++ programmers, written from experience of transitioning from C++ to Rust at Irreducible.

• Analyzed multi-source datasets using information-theory metrics such as permutation entropy, informational complexity, and decision-support models.
• Developed algorithms and data visualizations in MATLAB and Python.
• Conducted research and co-authored multiple peer-reviewed scientific publications based on the findings.
• Electrical project design and execution
• Digitalization and smart systems integration
• Supplier and contractor coordination
• Risk and quality management
• Strategic decision making
• Financial and ROI perspective
• Analytical and systemic thinking
• Data-driven decision support
• Problem solving and critical thinking
• Cross-functional team leadership
• Influential leadership

I worked on automating cold outreach.

• Developed a queue architecture to support the parallel execution of large volumes of background tasks.
• Integrated multiple email delivery providers.
• Implemented an LLM-based data enrichment process.

Technologies: TypeScript, React, Node.js, Next.js, Drizzle ORM, PostgreSQL, Next-Auth, JWT, Docker, Kubernetes, AWS, CloudFlare, Traefik, Groq, Jest, Figma

• Designed and implemented embedded firmware in C/C++ for ARM-based microcontrollers and SoCs (STM32, NXP, Infineon)
• Worked across bare-metal, FreeRTOS, and Embedded Linux environments, contributing to BSP-level functionality, driver bring-up, and system integration
• Built, configured, and validated Embedded Linux systems using Yocto, including image build, boot validation, and runtime debugging
• Developed and executed unit, integration, and system-level tests, including HIL and SIL test scenarios on real hardware and simulated environments
• Created Python and Bash scripts to automate build, test execution, simulation runs, and reporting within CI/CD pipelines (Jenkins, GitLab CI)
• Designed test cases from software and system-level requirements, covering normal operation, edge cases, and failure scenarios
• Performed low-level debugging using JTAG/GDB, analyzing boot issues, timing problems, interrupts, and peripheral behavior
• Developed and validated communication interfaces including UART, SPI, I2C, CAN using logs and external measurement tools
• Used simulation and virtual test environments to validate software behavior prior to hardware availability
• Read and interpreted hardware schematics to understand signal routing, pin multiplexing, and peripheral connections
• Supported PCB design and review activities using Altium tool, assisting with component selection, pin mapping, and bring-up readiness
• Collaborated with cross-functional hardware, firmware, and system teams to clarify requirements, document assumptions, and improve overall test coverage
• Developed web interfaces using HTML, CSS, and JavaScript (ES6) and basic REST API development with Node.js
• Experience testing web applications and building UI automation frameworks using Selenium WebDriver