Python Experts in Vienna

• Consulting and interim management at the interface between IT operations and regulation
• Impact analysis and implementation planning for NISG 2026 and the EU AI Act, including risk management and reporting and evidence processes
• Training for governing bodies and employees on regulatory obligations
• Lectures in Data & Information Management and Human-Machine Interaction at University of Applied Sciences Burgenland, since 2023
• Supervision of master’s theses and participation in the examination board
• Presentations for business and educational institutions
• Design and development of data and AI products, platforms and pipelines
• Privacy-first architectures and zero-knowledge encryption, cloud-native on EU infrastructure
• MLOps and AIOps in live operations
• Own applications under own brand: shared codebase, separate delivery for each target device
• AI-assisted software development (vibe coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
• Publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
• Publications on data sovereignty, cloud economics and industrial image processing
• AI governance / compliance: data quality, Responsible AI, EU AI Act readiness, risk classification, AI ethics

Technologies: Azure DevOps, Jira, Confluence, Office 365 (Teams, PowerPoint, Copilot, Excel, SharePoint, Forms, OneNote, PowerAutomate, Word), DataDog, Conceptboard, Python, AWS, Claude, Perplexity Methodology: Scrum

• Steering and supporting the organization in introducing Scrum and a SAFe-inspired quarterly roadmap and portfolio planning at program level.
• Servant leadership for Scrum teams and managers to achieve quarterly goals and measurably increase value creation for internal and external customers.
• Designing and building efficient communication and collaboration structures between multiple development teams and central stakeholders in the organization.
• Moderating and facilitating cross-functional workshops and management meetings to align on shared goals.
• Coaching leaders, Product Owners, and development teams on agile values, role understanding, and scaled ways of working (Scrum, SAFe, Business Agility).
• Removing structural obstacles at team and organizational level through targeted impediment management and escalation processes.
• Enabling teams to become more self-organized, accountable, and end-to-end responsible along the value streams.
• Individual coaching of key people (Product Owners, Chapter Leads, Scrum Masters) to strengthen their impact in the transformation program.
• Organization-wide identification, planning, and implementation of process, structure, and tool improvements to sustainably increase efficiency, throughput, and value creation.
• Close support for Product Owners in stakeholder management, business value prioritization, product strategy, roadmap planning, and effective collaboration with development teams.
• Introducing, governing, and scaling Azure DevOps as the central project and product management tool, including coaching the organization on usage, reporting, and alignment at all levels.

Achievements:

• Clear increase in visibility, transparency, and perceived value creation of the development teams within the overall organization.
• Noticeable improvement in communication between development, business, and other stakeholders.
• Optimization of work processes, workflow, and backlog structures, which reduced lead times, sharpened priorities, and sustainably increased team effectiveness.

Refactoring and improving core APIs; implementing client change requests. Setting up metrics, traces, and logs monitoring infrastructure to support operations. Designing GitOps deployment and infrastructure as code. Applications and systems configuration in ArgoCD and Openshift. Confluence documentation of design, approach, and solution. Tech Stack: Java 8 & 21, Spring framework, JSP, JavaScript, Bash scripts, SQL, Grafana Stack, OpenTelemetry, Docker, DB2, Maven, Kubernetes Kompose.

• Designed and built a next-generation NLP platform to accelerate sales-driven customer service through intelligent request analysis and routing, reducing average customer query response time by 30%.
• Architected a hybrid NLP system combining Large Language Models (LLMs) with traditional NLP pipelines for robust, explainable results.
• Developed request classification and routing mechanisms to accelerate customer support teams in handling customer queries faster and more accurately.
• Optimized LLM based data extraction and classification with context engineering.
• Integrated the platform into customer service processes, reducing response times and enhancing workforce efficiency.

• Extraction, transformation, and cleansing of data from Microsoft Dynamics AX
• Creation of sales reports in Power BI
• Training employees in business intelligence
• Technologies: Power BI, SQL, SQL Server Integration Services (SSIS)

• Develop AWS-based components connecting Python backend services to React/TypeScript frontends.
• Improve database queries and application workflows for document processing and screening.
• Evaluate LLM retrieval and document-review workflows as part of the product stack.

Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI

Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine

• Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
• Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
• Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
• Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
• Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
• Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
• Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).

Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock

Achievements:

• Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
• Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
• Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
• Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.

• Development of a charging station for electric vehicles
• Tools: C/C++/Matlab/Simulink
• Development and testing of functional software with various communication buses

• Foundational member of the backend TypeScript team, responsible for translating the initial product concept into a fully functional platform.
• Architected the core resource discovery engine for Azure and AWS, successfully enabling the frontend to visualize complex cloud environments and empowering the AI to evaluate architectural patterns.
• Engineered and scaled distributed APIs and dynamic CosmosDB schemas, ensuring the database and backend architecture could seamlessly adapt to rapidly evolving product requirements.
• Accelerated cross-functional testing by developing custom data-generation tools, allowing the AI and frontend teams to simulate and test against large-scale, artificial cloud architectures.
• Drove end-to-end feature delivery by partnering closely with AI, frontend, and business stakeholders to align technical implementation with the strategic vision of the Dawnguard platform.

• Teaching & presenting
• Communication
• Effectively communicate complex technical topics to non-technical audiences through lectures
• Guided non-technical students from zero knowledge to confidently understanding and applying algorithms to achieve business outcomes

• Architected and deployed a highly available, multi-tenant Kubernetes platform on Google Kubernetes Engine (GKE) for business-critical microservices.
• Designed and implemented a comprehensive Infrastructure-as-Code strategy using Terraform for managing GKE clusters, networking (VPCs, Subnets), and IAM policies.
• Engineered optimized storage solutions for stateful workloads (MongoDB) using GKE PersistentVolumes, enhancing performance and data resiliency.
• Established a full-stack observability framework using Google Cloud Monitoring, Logging, Prometheus, and Grafana.

• Supports CANCOM customers in migrating legacy on-prem systems to Microsoft Fabric and Microsoft Foundry
• Takes over and stabilizes existing solutions after a short handover
• Business analysis and requirements engineering for migration to a new cloud environment
• Optimization of machine learning models for feature extraction and customer profiling
• Ensures data protection and compliance
• Leads the migration of on-prem systems to Microsoft Fabric
• Designs new AI platforms for clients
• Tests the integration of chatbots for document intelligence with Microsoft Foundry, including requirements analysis, implementation, validation, and client communication

• Analysis of extended requirements related to existing controllers in an industrial plant
• Creating concepts for storing and visualizing sensor data
• Communication with PLCs
• Microservice architecture
• Unified architecture
• AI-based evaluations of sensor data
• Technologies used: .NET 8, Minimal API, Postgres, MQTT, RabbitMQ