Data Quality Experts in Berlin

• Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility

• Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture

• Pipeline orchestration with Azure Data Factory

• Improved and automated the development and deployment process by integrating Git and GitHub Actions

• Technical leadership of the Data Engineering team (3 employees)

• Led workshops to optimize and stabilize the data platform and development process

• Collected and prioritized new requests and maintained the product backlog

• Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural

Assignment focus: Leading digital restructuring in a highly regulated Defence and Aerospace environment. Focus areas: improving data flows and data quality, introducing paperless data collection in production, integrating machine data for automatic SPC calculation and process control, as well as cybersecurity analyses.

Main objectives:

• Analyze, structure and improve data flows and data quality in production
• Introduce paperless data collection in manufacturing areas
• Integrate machine data for automatic SPC data calculation and process control
• Implement digital restructuring while meeting regulatory requirements in the Defence environment

Measures and results:

• Analyzed and structured existing production data flows as a basis for control and reporting
• Established mechanisms to ensure data quality and availability across manufacturing areas
• Introduced paperless data collection in production — replacing manual and paper-based processes
• Integrated machine data for automatic SPC data calculation (control charts, Cp/Cpk) and real-time process control
• Conducted cybersecurity analyses in the production and IT environments

Area of responsibility: Project management for digital restructuring, paperless production, data management and data quality in a highly regulated Defence and Aerospace environment.

• Architected an enterprise Fabric-based data-product governance framework, authoring data contracts and schema-validation KPIs to enforce completeness, freshness and SLA standards across reporting data products.
• Operationalized pipeline observability by integrating Dagster orchestration data into automated data-health reporting, proactively validating data integrity and pipeline reliability before production reporting layers refresh.
• Established BI-as-Code and end-to-end governance through Git-based version control, CI/CD and Alpha→GA release management, strengthening lineage, schema-drift detection and production change traceability.

• 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.

• Detecting fraud patterns and implementing effective anti-fraud rules while maintaining acceptable false positive rates to ensure a balance between safety and a frictionless user experience
• Supporting ideation and roll-out of new trust and safety features to the platform to block fraudulent activity and increase user awareness for fraud
• Supporting Product, Development and Customer Support with BI reports and further guidance to identify and fight fraud and policy violations

• 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.

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.

• 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.

• 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.

• 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

Engaged as an independent BI consultant for a FinTech SaaS platform, building and maintaining the end-to-end Microsoft Azure and Fabric analytics stack behind a multi-tenant accounting product used by business owners to track their own financial performance.

• Partnered with finance stakeholders to translate complex accounting workflows into real-time BI dashboards (P&L, Cash Flow, Balance Sheet), helping 2000+ business owners track cash flow and overall financial health effortlessly.
• Developed 10+ interactive dashboards, giving each business owner personalized, real-time visibility into their own sales performance, accounts receivable aging, and operational costs.
• Enforced strict enterprise data governance by implementing dynamic Row-Level Security (RLS) via DAX to isolate each business owner's data within the shared multi-tenant model.
• Maintained and extended an Azure ELT pipeline (Azure Data Factory, Azure SQL Database, Azure Synapse) that automated data ingestion and transformation.
• Contributed to a team-wide platform migration from Azure to Microsoft Fabric to optimize capacity licensing costs.
• Designed and implemented a Microsoft Fabric ELT pipeline (Lakehouse, Pipelines, PySpark) that automated data ingestion and transformation, replacing the prior Azure pipeline.
• Modeled cleansed data into a Star Schema within the data warehouse using T-SQL, powering the Power BI Semantic Model.
• Leveraged AI tools, including Copilot and Claude, as development partners across the entire ELT pipeline, from data ingestion to KPI reporting and visualization.
• Supported agile delivery processes, using Jira to track development tasks and Confluence to maintain technical and project documentation.

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.

• Taught Python, Pandas, data analysis, visualization and Power BI to 250+ students.
• Guided practical projects from data preparation and exploratory analysis through visualization and dashboard creation.
• Explained complex analytical concepts clearly to audiences with different levels of technical experience.