Amazon Web Services Experts in Vienna

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.

• Built Enterprise Architecture practice covering business, application, data, and integration layers
• Created a multi-year Integration Strategy, delivering annual cost savings of several hundred thousand euros
• Defined portfolio simplification roadmap, identifying redundant systems and cost reduction opportunities
• Designed target-state enterprise architecture around D365 FSCM, enabling a best-of-breed future landscape
• Developed Master Data Management (MDM) strategy and roadmap to improve data quality and operational efficiency
• Provided enterprise-wide architectural direction ensuring alignment and eliminating redundant initiatives
• Established reusable architecture patterns adopted by delivery teams
• Facilitated cross-functional architecture forums to align product and delivery teams
• Translated enterprise architecture guidance into practical delivery decisions
• Drove practical adoption of architecture guidance across initiatives rather than acting as a gatekeeper
• Identified redundant systems enabling substantial cost reduction potential
• Enabled cost transparency in integration landscape
• Enabled fact-based investment prioritization decisions

• 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.

Owned the end-to-end architecture and the transition for the fourth licence period of the UK National Lottery: a complete technology stack replacement delivered against a hard regulatory deadline. Produced the end-to-end high-level architecture that served as the delivery baseline for the replacement of all major IT service components including infrastructure

Target architecture across two geo-redundant UK data centres: multiple VMware ESX clusters, OpenShift, MS SQL Server clusters, Oracle Exadata, integrated with AWS-hosted components and a retailer WAN over VSAT, DSL and LTE

Business continuity concept and geo-redundant high availability design

Review and approval authority over all low-level designs, application and infrastructure: network security, Oracle RAC, VMware, OpenShift, SQL clustering, geo-redundancy

Designed and implemented full hardware and network separation between test environments and staging/production

SME for third-party security audits against CIS benchmarks and NIST standards: preparation, execution, findings analysis, remediation prioritisation

Delivered software deployment to 45,000 retail terminals with minimal downtime, plus data migration from the incumbent end-to-end landscape to the new architecture

Transitioned 45,000 POS terminals and 19 million online players on time with no critical incidents

Owned the integrated transition plan for the full replacement of the lottery technology stack: work packages, milestones, dependencies and critical path across parallel technical sub-projects

Central organisational interface between internal IT leads, technical workstream leads, multiple external vendors and client executive stakeholders

Planned and led migration and cutover of live, regulated national infrastructure, including 80+ bare metal servers running VMware ESX, Microsoft VMs across several Active Directory domains, Linux VMs, OpenShift on Linux, 2 SANs, 2 Oracle Exadata systems, AWS components and a retailer WAN

Ran 4 full cutover dress rehearsals ahead of the 2 major go-live releases

Governed all changes through the ITIL change process and CAB; ran risk, issue and escalation management with regular status reporting to the Program Director and client's CTO

Onboarded the internal cyber security team and acted as architecture SME in pre-deployment security audits for client and internal security teams, including prioritisation and remediation of findings

Joined the programme as Enterprise Architecture Lead from May to September 2022, gaining detailed knowledge of the target infrastructure before taking overall delivery responsibility; after go-live, supported the delivery teams through the warranty phase

• 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.

• 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)

Replacement of HR BW system

Industry: Automotive

Technology: SAP Datasphere, SAC, Cloud Integration, CAP Application, Databricks

• Development of the target architecture to transform the existing BWonHANA HR BW to SAP Datasphere
• Development of an authorization concept
• Execution of architecture governance in the implementation project

• Shaping service management framework as part of head office of RBI
• Service owner overseeing IT cloud services, accountable for overall quality, lifecycle, and success
• Managing customer relationships and satisfaction for 10 business units ensuring smooth business continuity and operations
• Single point of contact and service/process owner providing T-shaped expertise in IT domains, cloud platforms and services (AWS, Azure, Kubernetes, Salesforce, ServiceNow, Jira, Orca, CRM, GitHub, SFMC)
• ITSM/ITIL implementation and mentoring including design, definition, mapping, and execution
• Change and release management, UAT/test assurance, major incident management, SDLC management
• Managing regulatory and audit requirements, DORA, GDPR, ITPF compliance and reporting
• Acting as a point of escalation for complex customer issues, resolving conflicts, fostering a customer-centric culture
• People management: leading and managing service delivery teams, DevOps, vendors, and third-party teams
• Cross-tribe service delivery and contract management: KPIs, SLAs, OLAs, RPO, RTO, BCM/SCM management
• Agile/Scrum process delivery governance, stakeholder communication, and budget/cost management

• 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.

• Architected enterprise AI strategy delivering 25% cost reduction through multi-LLM platform integration (Claude, OpenAI, Gemini) with intelligent routing and fallback optimization
• Drove operational excellence achieving 85% reduction in manual documentation and 3x faster campaign production through AI workflow automation and agent deployment across Slack and Microsoft Teams
• Established AI governance framework from ground up, implementing EU AI Act compliance, data redaction protocols, and safety filters aligned with DPIA standards
• Scaled AI adoption through structured onboarding programs, developing departmental workflows with secure access controls and comprehensive audit trails
• Implemented advanced RAG systems using Elasticsearch, Vertex AI, and Azure AI Foundry to improve knowledge access and output reliability
• Managed delivery through OKR framework coordinating cross-functional squads across 6-week project cycles to ensure strategic alignment and measurable results

• Conducting a feasibility study on introducing an in-house DWH as a central data source
• Conducting workshops for current state analysis (processes, reports, KPIs) together with the clients
• Gathering and detailing business requirements including a target concept for an in-house DWH
• Coordinating and clarifying data deliveries and interfaces in meetings with stakeholders and data providers
• Developing initial data models as a basis for data quality and later implementation
• Drafting solution variants including architecture and operation options and decision basis
• Creating the business case including effort estimates, cost-benefit analysis, and decision report