Cloudera Experts in Germany

• Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
• Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
• Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
• Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
• Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
• Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
• Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
• Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.

Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:

• Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
• Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
• Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
• Conceptual support for the development of an integrated reporting and performance management setup
• Execution of customer insights analyses to identify patterns and anomalies within customer data clusters

Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:

• Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
• Strategic-operational consulting for the introduction of RELEX including best practices
• Support in defining overarching goals and requirements (2-year target picture)
• Guidance in scoping a relevant supply chain network segment for the project
• Development of a roadmap for iterative, incremental RELEX setup and rollout
• Assessment of project dependencies (interfaces, configurations, etc.)
• Advice on prioritized implementation of business requirements and data interfaces
• Support in test planning (data validation, system testing, UAT)
• Consulting on internationalization, change management, training, and knowledge transfer
• Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX

Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:

• Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
• Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
• Proposal of quality improvements for program and modernization efforts
• Sparring partner and professional, technical, structural and organizational consulting for project and program management

Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:

• Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
• Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
• Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
• MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)

Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:

• Coaching of the core team with topic managers and team leads
• Introduction to the OKR topic and setup of the OKR cycle
• Establishment of the OKR approach in teams and on a cross-team level

Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:

• Analysis of current challenges
• Definition of overarching goals
• Development of a proposal for a new team structure
• Identification of required competencies, skills and responsibilities
• Advisory and alignment on communication and change management strategy

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment

• Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
• Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
• Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
• Use of Scrum and Kanban methods.
• Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
• Development of new plugins and add-ons needed on current infrastructure.
• Database support.
• Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
• Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
• Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
• Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
• Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
• Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
• Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
• Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
• Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
• Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
• Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
• Automated system provisioning and deployment using CloudFormation templates.
• Configuration of IAM roles, policies and permissions to ensure secure access control.
• Patch management, backup automation and disaster recovery setup on AWS infrastructure.
• Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
• Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
• Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
• Configuration of AWS CloudWatch to monitor application performance and system events.
• Planning and execution of migration of on-premises applications to AWS cloud platforms.
• Deployment of containerized applications using Docker and Kubernetes in AWS environments.
• Deployment of internal software packages between availability zones using AWS CodeDeploy.
• Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.

• Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
• Independently designing analytics solutions with Python, SQL, etc.
• Designing and implementing ETLs and data pipelines
• Creating and maintaining APIs
• Independently applying CI/CD, testing, and version control
• Data modeling
• Model development and optimization
• Anomaly detection with AI
• Predictive analytics

Used technologies:

• Snowflake
• Fabric
• Azure Synapse Analytics
• Azure DataFactory
• Azure Data Lake
• Azure DevOps
• Databricks
• Spark
• CI/CD
• SQL Database
• Python
• Power Platform

• Led the end-to-end delivery of a SAP Supply Chain Management (SCM / TD / SD) ERP programme, covering project initiation, detailed requirements gathering, operating model definition, system design, build, testing, cutover, and global Go Live across Europe, Asia, and North America. Ensured the ERP solution supported key supply chain, manufacturing, and planning operations to enable future business growth.

• Conducted cross-functional workshops with Supply Chain, Procurement, Planning, Manufacturing, and Logistics teams to capture business requirements, define the future operating model, and map end-to-end system design. Consolidated over 150 requirements into structured documentation aligned with SAP standards.

• Shaped solution design and vendor engagement during the early discovery phase, supporting selection of best-fit technology partners and ensuring the system design covered production planning, inventory management, warehousing, logistics, and supply chain forecasting.

• Managed D365 configuration and troubleshooting, ensuring alignment with business processes and resolving integration issues between D365, SAP SCM modules, and surrounding systems.

• Supported Grain data model changes to lead ingestion of planning data into Snowflake and Footprint, enabling enterprise reporting and analytics development.

• Managed scope, timelines, risks, and dependencies across international teams spanning Europe, Asia, and the US, maintaining integrated project plans, issue logs, and executive reporting to drive stakeholder alignment and delivery momentum.

• Enabled the integration of AI-powered demand forecasting tools into supply chain planning processes, improving forecast accuracy, inventory turnover, and operational decision-making across multiple regions.

• Led SIT, UAT, and data migration phases, including design of test scenarios, defect triage management, and coordination of test execution to validate supply chain and manufacturing workflows prior to deployment.

• Delivered detailed cutover planning, business readiness activities, and hypercare support, ensuring a smooth and coordinated Go Live and full operational handover to business teams.

• Developed a retrieval-augmented generation (RAG) application using LangChain and LangGraph for corporate document parsing, delivered as an installable Electron desktop application with local AI models via Ollama.
• Currently providing ongoing AI feature support for the Loan Pricing Tool at Hamburg Commercial Bank, with a commitment of three days per month.
• Architected Kubernetes-native solutions, including Helm chart configuration and Azure DevOps pipeline integration.

• Hands-on product and portfolio analyses with actionable recommendations
• Skilled in consulting, concept development, and agile project management
• Technical leadership & team empowerment – for smooth agile delivery with foresight and guardrails

• Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
• Performance Optimization of Data Ingestion of ETL Pipeline
• Development of Data Validation using Great Expectations
• Leading of the data migration for two sources exchanges
• Data Modeling in AWS Redshift

MLOps

• Model inference implementation by mlflow and AWS SageMaker
• Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
• Implementatino of Model Registry and artifactory using mlflow
• Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
• Feature importance using mlflow

Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy

• Developed the AI strategy for a major Austrian retailer with over €10 billion in annual revenue.
• Developed a go-to-market strategy for AI services for a Norwegian consulting firm specializing in SAP technologies.
• Delivered AI for Business training programs to a leading German supermarket chain.
• Defined AI governance project structure and roadmap for a large German manufacturer.
• Certified facilitator for AI Design Sprint™, leading use case discovery workshops for large enterprises.
• IEEE Certified AI Ethics Assessor with expertise in building AI governance frameworks aligned with the EU AI Act.
• Founder of aiethicsassessor.com as knowledge base for AI governance and AI legislation.
• Author of a best-selling Udemy course on Data Architecture.
• Developed intelligent agents using low-code/no-code platforms to automate complex business processes.

• Designed and implemented a scalable data lake on Google Cloud Platform (GCP) for the Anti-Financial Crime (AFC) division, supporting Anti-Money-Laundering and Counter-Terrorism-Financing initiatives

• Built robust data pipelines for ingesting and processing over 30 million daily transactions from retail and corporate banking, applying dimensional modeling to enable advanced analytics and regulatory reporting

• Ensured resilience by implementing change data capture, late-data handling, and schema evolution across evolving source systems

• Led a small engineering team and collaborated with international stakeholders in Germany, Singapore, Sri Lanka, Hong Kong, Taiwan, and Thailand to ensure compliance, data quality, and performance

• Google Cloud Platform (GCP)

• Apache Spark (Dataproc & Cloudera Data Platform - Python PySpark)

• Apache Airflow (Cloud Composer - Python API)

• Google Cloud Storage

• BigQuery

• GitHub Actions

• Terraform

• Google Kubernetes Engine (GKE)

• Global marketing analytics for Hitachi Energy as part of a global data modernization initiative aiming to enhance data retention, historical data availability and provide Eloqua's 2-year retention for remote interaction reporting and analytics.

• Analyzed Eloqua's default retention policy and identified risk of data loss for records older than two years.

• Designed and implemented historical data preservation strategy by creating transformed tables in the target data platform to archive older data while ensuring data quality dashboards.

• Collaborated with the Power BI team to re-point dashboards from raw Eloqua imports to the newly created archival layer.

• Leveraged Jira to track and manage data engineering tasks, bugs, and feature requests across Agile sprints; coordinated backlog prioritization and task assignment to align data pipeline development with business needs.

• Power BI dashboard optimization:

• Worked closely with business stakeholders to assess and understand reporting needs for reverse customer data.

• Designed and implemented incremental refresh in Power BI to ensure daily updates without full data reloads.

• Collaborated with Azure data engineers to optimize data processing and publication pipelines.

• Stakeholder communication & data modeling:

• Acted as liaison between Group Data Office and Technology Office to align data modelling standards.

• Gathered requirements from data engineering team and participated in weekly status meetings to provide implementation updates and resolve blockers across teams in Germany, Poland, and India.

• Documentation & quality assurance:

• Prepared end-to-end technical design documentation, data flow diagrams, and Power BI audit guides for future reference.

• Participated in UAT sessions with business users to validate data outputs and report accuracy.

• Refactoring a legacy energy data management system: migrating the original architecture to an event-driven microservices architecture; time series management of energy data; close collaboration with the data science team to develop novel machine learning and AI approaches for energy forecasts and schedules; implementation of cross-organization machine-to-machine communication; containerization up to private cloud

• E-mobility and green hydrogen projects: intelligent energy distribution for simultaneous charging of multiple vehicles; optional sale of energy or green hydrogen production depending on market price; implementation of machine-to-machine communication with partners

• Smart city / residential quarter management projects: implementation of machine-to-machine communication with the smart city/residential quarter platform; testing of suitable architectures; platforms: Bauhaus Mobility Lab (Sensor Things API); ODH-Jülich (BASYX Asset Administration Shells); SMOOD on Camunda; Fiware Context Broker

• Data spaces / International Data Spaces projects: transfer of time series using IDS connectors; building expertise in Gaia-X compliant data spaces (Eclipse Data Components, XFSC, Tractus-X; decentralized identifiers; data sovereignty; standardized APIs and data objects; requirements for Gaia-X compliant data spaces); Avatar project (anonymization of personal health data)

• Technologies used: Java; Spring Boot; Spring Cloud; Apache Kafka; REST APIs; Keycloak; Grafana + Loki; Oracle; PostgreSQL; MongoDB; Gradle; deployment on Ubuntu Server using Docker, docker-compose, Google Distroless

• Project organization and responsibilities: agile based on Scrum; hybrid; working in interdisciplinary teams across organizational boundaries; making architecture decisions; leading and mentoring research assistants and interns

• Work model mainly home office

• Technical consulting for greenfield development of AVIATAR 2.0
• Designing data pipelines and data architecture within the DataVerse Data Lake
• Planning and implementing Data Lake zones, data governance, data retention, and recovery strategies
• Collaboration with the Data Architecture and Platform Team for infrastructure scaling and design
• Close cooperation with stakeholders across Lufthansa Technik, including requirements management
• Hands-on development of data pipelines using Spark Structured Streaming and Databricks
• Proofs of Concept (PoCs) for Graph-Links and real-time analytics
• Provisioning data for AI and ML projects (e.g., predictive analytics)
• Technical design and implementation of near-real-time pipelines based on business requirements