Shell Scripting Expert in Berlin

• Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.

• Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.

• Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.

• Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.

• Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.

• Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
• Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
• Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
• Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
• Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
• Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
• Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.

• Azure Landing Zone architecture: Design and implement a hub-spoke, multi-region-capable Azure landing zone that provides the secure, scalable and highly available foundation for autonomous driving and parking data/ML platforms.
• Compliance through Azure Policy: Enforce security and compliance standards across Azure subscriptions via Azure Policy (guardrails, deny/audit/deploy-if-not-exists), consistently achieving top-tier infrastructure security scores.
• Infrastructure-as-Code: Automate provisioning and configuration of Azure resources with Terraform and Bicep, with changes delivered through reviewed CI/CD pipelines.
• Azure Databricks and Unity Catalog: Extensive experience operating Azure Databricks with Unity Catalog for centralized data governance, access control, lineage and auditing across workspaces.
• Monitoring and observability: Built and run infrastructure monitoring and logging with Azure Monitor, Prometheus, Grafana and Loki, covering platform health, alerting, troubleshooting and capacity trends.
• Platform at scale: Architected and operate cloud data/ML platforms supporting multi-PB vehicle data ingestion and simulation; orchestrate Argo Workflow-based recompute and autolabeling services scaling to 100k+ concurrent pods on AKS.
• Reproducible ML: Established reproducible training environments with dataset versioning and provenance tracking, enabling auditing and experiment reliability.
• Operational excellence: Automated GitHub organization management and CI/CD pipelines, improving developer productivity and deployment reliability; automated recurring operational processes.
• FinOps: Developed transparent resource utilization and cost-tracking for multi-project Azure environments.
• Leadership: Technical lead for infrastructure topics, collaborating with development, DevOps and security teams; technical interviewer and recruitment panel member for scaling the engineering team.

• Developed a Flutter app for eID ID card logins
• Focus: Flutter, iOS, eID, AusweisAppSDK, Mason, Keycloak, Agentic Coding, Arc42, Jenkins

• 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.

• IT training in theory and practice for IT specialists in application development and system integration

• Manage the development release and update process for a digitized nationwide trade register project "AuRegis".

• Support software in Kubernetes/OpenShift environments, configure management with Kustomize, and implement CI/CD pipelines using Jenkins/GitLab, SonarQube, ArgoCD, and Azure.

• Oversee system release of microservice architecture.

• Build the CI/CD stack from scratch with GitLab CI, integrating integration tests, dependency checks, and security measures.

• Automate deployment onto OpenShift using Kustomize.

• Set up infrastructure components for development, code review, and code quality analysis including SonarQube.

• Integrate GitOps tools such as Kustomize and ArgoCD, using both Azure and private cloud for sensitive data handling.

• Develop Python scripts in Jenkins for cryptostore configuration and system packaging of products and microservices into deployable units.

• Automate delivery to customers and deployment on test systems.

• Create Kustomize manifests for microservices and develop the related automation, treating documentation as code for clarity and reproducibility.

• Serve as technical advisor for the project's first go-live and oversee further deployments as technical rollout manager.

• Projects for federal networks (NdB).
• CR management, EoL change requests, design and documentation according to ITSCM.
• Data center planning.
• Project management and engineering subproject management.
• Software development for virtual server environments according to BSI.

• Development of control units for the automotive industry incl. embedded software
• CAN bus, Vector Tools, CANoe
• Support of the development process according to ISO 26262
• Ensuring cyber security standards:
• Key exchange (PKI) between vehicle and control units
• Hardware Security Module (HSM)
• Communication with external service providers (international)
• Development (PCB) of measuring adapters, statistical analysis of sensors
• IoT and embedded software development, backend administration

• 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

Projects:

Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:

• Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
• Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
• Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
• Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
• Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
• Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management

Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:

• Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
• Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
• Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
• Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
• DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
• Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
• Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git

• Developed a Proof of Concept for distributed tracing using OpenTelemetry within a microservices architecture, enhancing system observability and reducing mean-time-to-resolution for issues.
• Built and maintained backend services using Java and Spring Boot, ensuring high reliability and performance for payment transaction workflows.
• Implemented comprehensive automated testing with JUnit and Mockito, achieving 95% test coverage to ensure code quality and maintainability.
• Gained insight into payment transaction workflows, validating end-to-end system reliability and gaining domain knowledge in financial processes.
• Tech used: Java, Spring Boot, Microservices, REST API, Kafka, Grafana, Datadog, Docker, MongoDB

• Database administration and performance tuning for Oracle databases on AIX 7.1, 7.2 with Oracle 12c and 19c
• Troubleshooting and resolution on RHEL 7
• Automation of operations with UNIX/Linux shell scripts, Perl programs, and PL/SQL
• Planning, preparation, execution, and customer-specific review of changes and upgrades for the LEASMAN and DOXIS applications
• Incident handling including communication with outsourcing service providers and business units
• Data exchange with Data Pump
• Visualization of database content and monitoring results
• Configuration of databases for Debezium and monitoring Debezium activities
• Preparation of Oracle databases for migration to cloud environments
• Implementation and monitoring of NIST requirements in databases
• Automation of release upgrades for the LEASMAN application
• Creation of operations manuals and instructions
• Generation of reports for GDPR information requests

• Designed, implemented, and evaluated multiple machine learning models (e.g., regression, time series, neural networks) to forecast cryptocurrency prices, incorporating data preprocessing, feature engineering, and model optimization for improved predictive accuracy.
• Performed in-depth data exploration and visualization on large cryptocurrency datasets, using tools like Python and libraries such as Pandas and Matplotlib to identify trends and patterns.