Data Quality Experts in Berlin

• Used OpenCode and AI-assisted software engineering to design, implement, refactor, test, and document an end-to-end RAW/SDTM/ADaM pipeline in R for Dr. Falk Pharma (07/2026), including metadata-driven transformations, automated validation rules and QC, traceability, and reproducible clinical outputs.

• Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
• Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
• Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
• Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.

• Designed and developed AI-powered document processing solutions using Python, OCR, NLP, and Large Language Models (LLMs) to automate extraction, validation, and classification of financial documents, reducing processing time by 75%.
• Built intelligent multi-stage workflow automation pipelines integrating AI services, machine learning models, and enterprise systems to streamline financial operations and improve data quality.
• Developed reusable AI-driven transformation frameworks capable of processing structured and unstructured document formats (XML, CSV, JSON, TXT, DAT) and normalizing them into unified business schemas.
• Designed and developed Python-based REST APIs and backend services supporting enterprise finance applications and high-volume data processing workloads.
• Built scalable data synchronization pipelines between Oracle CFIN and SQL databases, incorporating machine learning models for cash-flow forecasting and AP/AR anomaly detection.
• Architected and deployed Apache Airflow workflows to orchestrate AI-powered data pipelines, automating end-to-end processing from document ingestion through financial system integration.
• Led the migration of critical enterprise integrations from MuleSoft to Python-based services, improving maintainability, performance, and operational flexibility while preserving complete data integrity.
• Managed the full API lifecycle including solution design, implementation, documentation, deployment, monitoring, and production support for mission-critical financial systems.
• Collaborated directly with finance stakeholders to identify business challenges, define solution requirements, and deliver measurable operational improvements through automation and AI-driven workflows.
• Worked closely with cross-functional engineering and business teams to rapidly iterate on features, improve processes, and drive successful adoption of AI-enabled solutions.
• Provided technical leadership through architecture reviews, technology decisions, code reviews, and engineering best practices across integration and automation initiatives.
• Mentored developers, established coding standards, and contributed to improving software quality, maintainability, and delivery effectiveness across projects.
• Provided production support during critical month-end and quarter-close financial processes, performing root-cause analysis and implementing rapid fixes to ensure system reliability and data accuracy.

• International expansion & segment strategy: Built Germany footprint from zero, scaling to 1,000+ SaaS customers across four European markets, developing vertical value propositions, use cases, and segmentation models
• Planning, OKRs & single source of truth: Designed forecasting frameworks, pipeline diagnostics, territory/quota structures for a 30+ FTE commercial org, and established OKR-driven execution with shared dashboards and decision logs
• Operational excellence, automation & regulated delivery: Applied Lean Six Sigma methods and implemented automation and AI tooling across CRM and reporting, simplifying end-to-end workflows and reducing manual effort by ~25%
• Growth enablement & CX: Owned cross-functional growth experiments that increased activation by 30% and DAUs by 10% in a hybrid PLG + enterprise model
• Change management & cross-functional execution: Set KPI agreements with shared services, championed internal change programs, and drove adoption of new operating rhythms and tooling
• Risk management & portfolio steering: Established risk-aware customer prioritization and partnered with risk and finance teams on portfolio steering and resource allocation

Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.

• Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
• Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
• Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
• Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
• BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.

Built and scaled a high-performance enterprise API for real-time address validation and data quality with sub-second latency and 99.9 % availability.

Designed and integrated the solution into e-commerce, checkout, and logistics processes of leading European companies. Reduced delivery errors and shipping costs through automated data correction and precise data validation.

End-to-end responsibility for product strategy, technical architecture, software development, enterprise customers, operations, and GDPR-compliant data processing. Combined AI-native engineering workflows, Python, SQL, API integration, data quality, and workflow automation.

• Led development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
• Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
• Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
• Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
• Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
• Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.

Consumer Cards Solution Architect

• Provided architectural leadership in Consumer Cards Domain establishing best practices and improving architectural transparency and maintainability by designing a structured documentation framework to enable reverse engineering of legacy card systems.
• Standardized architectural artefacts including BIAN Business Capabilities, UML diagrams in draw.io format (Use Case, Component, Sequence), naming conventions, document repository, design templates and blueprints, microservices.
• Produced high-level and low-level designs aligned with enterprise architecture governance processes and artefact standards.
• Provided architectural support to the Strategic Card Simplification Programme, focusing on card product migrations and application decommissioning across all countries. Agile environments (Scrum/SAFe).
• Analysed and designed AI use cases in the architecture domain.

Project: Payment Card Industry Data Security Standards (PCI DSS) Strategic Programme

• Analysed and documented existing data flows across card products and geographic regions to assess PCI DSS compliance.
• Identified areas involving sensitive data at rest and data in motion requiring encryption or masking, ensuring adherence to PCI DSS requirements.
• Collaborated with security, infrastructure, and application teams to align encryption strategies with regulatory and organizational policies.
• Provided strategic advisory services on data strategy, data governance, data management, data quality, data architecture, data mesh, MEGA HOPEX, DAMA-DMBOK, event-driven architecture, end-to-end data flows and card product harmonization models.
• Ensured solution design alignment with regulatory compliance (BCBS 239, DORA, GDPR) and internal policies.

Project: Denmark ATM Outsourcing Project

Objective: Outsource ATM operations and maintenance to a third-party provider while expanding the Denmark ATM fleet, with Nordea retaining ownership of ATMs and cash for the existing and extended infrastructure.

• Led a cross-functional delivery team (project management, business analysis, and architecture) and documented the as-is ATM ecosystem architecture, including end-to-end data flows, integrations, and internal/external application interfaces.
• Designed end-to-end processes for authorization, reconciliation, and settlement, aligning operating model, controls, and compliance requirements across Nordea and the outsourced service provider.
• Produced high-level and low-level solution designs using standardized UML artefacts (Use Case, Component, and Sequence diagrams) to support vendor onboarding, integration planning, and implementation.
• Ensured architectural alignment and decision-making across enterprise stakeholders and third-party providers, managing dependencies and interfaces in the context of the outsourcing initiative.

• Lead a team of 15 annotators on large-scale computer vision projects for autonomous vehicle systems
• Developed comprehensive annotation guidelines that improved inter-annotator agreement by 35 percent
• Implemented quality control processes that reduced error rates by 42% across all projects
• Collaborated with ML engineers to identify edge cases and improve dataset quality
• Managed annotation projects for Fortune 500 clients, delivering 100% on time

Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.

Activities:

• Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
• Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
• Developed automated data pipelines with Python, dbt, and GCP services for different data sources
• Built monitoring and alerting systems for real-time platform monitoring
• Implemented data versioning and quality checks at every layer
• Designed automated test and deployment pipelines in GitLab and Bitbucket

Achievements:

• 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
• Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
• Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
• Migrated 7 database tables with 0 downstream issues
• Removed 100% exposed credentials, eliminated external vendor dependency
• Delivered integration of 3 teams in 1 sprint

• Developing methods for monocular 3D facial reconstruction and personalized geometric modelling from mobile imagery
• Building learning-based approaches for facial shape estimation, video-based facial analysis, and privacy-preserving visual learning

• Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
• Data and trade architecture development for liquidity provision

• Interim Product Owner for two new applications as part of the introduction of a new bonus points program within the entire Rewe Group
• Coordination of cross-team planning (initiative management) and implementation
• Responsibility for product vision, roadmap, backlog and stakeholder management within an agile scaled product development team
• Successful Go Live with both applications on 2024-09-24