PostgreSQL Experts in Vienna

I build. I advise. I think in systems. After years leading digital transformation at scale — Accenture, BP, Lidl — I made a deliberate choice: trade platform dependency for structural independence. My focus is at the intersection of AI systems, product strategy, and venture thinking. I work with operators and founders who want to move fast without losing control — of their data, their stack, their direction.

• Analysis of existing work, information and decision-making processes.

• Identification and prioritization of suitable use cases for AI agents.

• Elicitation of functional and non-functional requirements.

• Design of collaboration between users and AI agents, including control and escalation mechanisms.

• Support for the implementation of the AI agents and adapted keyboard hardware.

• Business target vision for the AI-first transformation.

• Structured and prioritized requirements for implementation.

• Defined roles, interactions and control points between people and AI agents.

• Preparation for the gradual automation of productive work processes.

Techstack: AI agents, LLMs, agent orchestration, RAG, APIs, automation, hardware

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.

• Business analysis
• Requirements engineering
• System design
• Various insurance projects
• Technology stack: msg.Billing (InExkasso)
• Product: Pay-per-use car insurance based on blockchain and OBD-II real-time telemetry with AI

• 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.

• Took Dawnguard from initial product concept to a launched MVP within two months, building the backend platform and reducing cloud-environment scan times from approximately 40 minutes to under two minutes across 70 accounts.
• Designed and built the core resource discovery engine for Azure and AWS, enabling the frontend to visualise complex cloud environments and the AI to evaluate architectural patterns.
• Engineered distributed APIs and dynamic Cosmos DB schemas to support rapidly evolving product requirements and variable cloud-environment structures.
• Built the architecture-generation engine to support clients with 100+ cloud accounts and dynamically generate complete architectures containing approximately 25,000 resources.
• Developed custom data-generation tools that enabled the AI and frontend teams to simulate and test large-scale cloud architectures.
• Delivered backend features end to end by working with AI, frontend, and business stakeholders from technical design through implementation and testing.

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.

Implementation and operation of OpenShift / Kubernetes solutions for customers, focusing on aspects such as storage, virtualization, security, logging, monitoring, and high availability. Support with application containerization and modernization.

• Project Lead, Sr. BI Expert, Data Scientist, Automation Engineer for Marketing Analytics | Customer Insights (retail, e-commerce)
• Product Manager: Asset Metadata Ingest & Provide
• Product Owner Business Intelligence – responsible for 2 teams: cloud data engineering, data warehouse (logistics)
• Product Owner for setting up a reporting platform on Azure & Power BI (finance)

• Design and deploy production multilingual AI voice-agent solutions for customer service, lead capture, after-hours support and front-office automation use cases.
• Delivered three client implementations spanning Europe, Asia and North America, including multilingual support, sales/lead-capture and privacy-sensitive intake workflows.
• Translate business requirements into conversation flows, prompt architecture, knowledge grounding, fallback and handoff logic, guardrails, consent gates and structured data capture; production support deployments include knowledge bases of approximately 1,000 grounded Q&A entries per language.
• Build scenario-based evaluation and regression QA covering normal flows, edge cases, failure modes, handoff behaviour and acceptance criteria; coordinate fixes through production readiness and rollout.
• Work hands-on across Retell, ElevenLabs Agents, Twilio, Supabase/PostgreSQL, Vercel, APIs/webhooks and CRM workflows; lead discovery, demos, solution shaping and cross-functional delivery.

Sector: AI voice automation / customer workflow design

• Creation of test scenarios, manual test cases and test data using boundary value analysis and equivalence partitioning
• Execution of functional and non-functional tests (manual with Postman and web application, automated with WebDriver, JUnit and NUnit)
• Setup, automation and maintenance of the Test Automation Framework with Java, Spring Boot, Selenium and Cucumber in IntelliJ (system, regression, smoke, UI and integration tests for web frontend and SOAP API backend interfaces)
• Automation of backend NUnit test cases in Visual Studio
• Test management: development and implementation of the test strategy and test plans, test coordination, quality responsibility and prioritization of risk-based tests, as well as documentation management in Confluence
• Detailed analysis and quality assurance of requirements
• Creation and maintenance of Jenkins pipelines, quality assurance during build & deployment
• Close cooperation with business analysts, developers, testers and test management
• Identification, creation and tracking of errors/defects, as well as careful test documentation
• Reporting of test results and defect reports
• Monitoring of test processes and continuous improvement
• Verification of test data and test results in a PostgreSQL database in pgAdmin
• Support with effort estimates and backlog prioritization
• Analysis and debugging of development code

System environment: Java, JUnit, Spring Boot, Selenium, Cucumber, JavaScript, Jenkins, C#, NUnit, Postman, Bitbucket, Confluence, Jira, xRay, pgAdmin, PostgreSQL, SonarQube, Maven, IntelliJ, Visual Studio, CI/CD, SOAP API interfaces

• Design, authorship and finalization of the IT PROD SEC service catalog with eight standardized security services (S-ID001–S-ID008).

• Development of consistent service components & deliverables, RACI assignments and SLA and KPI definitions for each service.

• Integration of BaFin document requirements under DORA into the service descriptions.

• Coordination with IT, compliance, risk and operations teams to validate all service descriptions.

• Specifically for governance & monitoring: definition of governance cadence, evidence delivery processes, audit support and definition of measurable KPIs and measurement methods.

• Ensuring that all services are standardized, measurable and documented in an audit-proof manner.

• Result: Approved service catalog with eight services as a binding basis for delivery, governance and audits; transparent SLAs/KPIs for each service and DORA/BAIT/MaRisk-compliant documentation with clear responsibilities and evidence trails.

• Technologies and tools: Confluence, Jira, ServiceNow, Microsoft PowerPoint, Microsoft Visio, Office 365.

• 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