Apache Hadoop Experts in Berlin

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.

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

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

• Provide the Price Listing Service team with prices for all cars and vans in different markets
• Adapt market-specific requirements such as taxes, government subsidies, campaigns
• Import and synchronize new prices for all new and existing cars and store them in the Redis datastore
• Support our product and on-call duty
• Daily business, development of new features, bug fixing
• Pair programming, code review, mob programming
• Develop POCs for new ideas
• Maintain and extend the backend
• DevOps tasks
• Run Kubernetes updates
• Adjust and further develop Kubernetes resources
• Develop and adapt Helm charts
• Adapt and update ArgoCD
• Maintain, adapt, and improve CI/CD

• Proceeding what was started in 10/2023, offering data science development skills fulltime to international clients

• Helping companies learn more about their existing (unstructured) data, optimize processes and technical systems, and derive solutions for their problems

• Tools and technology used: Python (sklearn, pandas, numpy, Django, sqlAlchemy, pyTorch), Matlab, Docker, AWS EC2, Lambda, S3, SQL, MySQL, Hadoop & Spark, Machine Learning, DNN, AI, Jira, Confluence, Git, CI/CD, GitLab, Jenkins

• Leading coordination between business units and IT
• Coordinating development and testing
• Business analysis and structured requirements gathering
• Specifying functional and technical requirements
• Integrating interfaces to internal systems
• Developing SQL queries and reports
• Documentation in Confluence Result: On-time go-live, structured and agreed project basis, ensuring a coordinated project workflow.

• Product strategy & vision: Led campaign performance reporting platform serving 700+ partners, transformed manual MSTR-based weekly reporting to real-time self-service platform enabling partner autonomy and operational efficiency
• Strategic roadmap management: Led phased migration prioritizing Performance campaigns (70% revenue) ahead of Awareness and Engagement, driving iterative platform evolution aligned with objectives, partner feedback, GDPR compliance, and data retention policies
• User research & customer discovery: Conducted regular user interviews with partners to understand reporting needs, decision-making processes, and additional KPI requirements, translating insights into platform enhancements and feature prioritization
• Cross-functional leadership: Collaborated with Product Consultants, analysts, data engineers, frontend teams, and product marketing to execute seamless platform migration, reducing PC team size by 2 FTEs while improving service quality
• Scaled user adoption: Strategically onboarded partners starting with top 30 partner-program partners, expanding to all 700+ partner-program and wholesale partners through user education documentation, training coordination, and iterative feedback incorporation
• Data-driven product optimization: Implemented Google Analytics tracking and engagement monitoring, identified low-engagement features (report downloads, detailed links), deployed AppCues and re-education campaigns resulting in 40% weekly engagement rate
• KPI standardization & governance: Led cross-functional initiative to standardize KPI definitions and formulas across reports, dashboards, and ZMS platform, defined North Star metrics and essential KPIs for each campaign objective ensuring consistent measurement and decision-making

• As a Data Specialist, I leveraged analytical expertise to transform raw data into actionable insights, driving strategic decision-making and operational improvements. My role encompassed data interpretation, reporting automation, and cross-functional collaboration, utilizing advanced tools such as Microsoft Excel, Power BI, and Python for comprehensive data analysis.
• Implemented Python scripts to validate and reconcile large datasets, reducing manual errors and improving data reliability.
• Utilized Python (Pandas, NumPy, Matplotlib/Seaborn) to automate data cleaning, analysis, and visualization, improving efficiency and accuracy in reporting.
• Developed interactive dashboards in Power BI to present key metrics, trends, and performance indicators, facilitating real-time decision-making.
• Designed and executed automated reports using Excel (Pivot Tables, Power Query, VBA) and Power BI, ensuring data accuracy and consistency across departments.
• Data Analysis: Excel (Advanced Pivot Tables, Power Query), Power BI (DAX, Data Modeling), Python (Pandas, NumPy, Visualization Libraries)
• Automation & Reporting: Power BI Dashboards, Excel Macros (VBA), Python Scripting.

Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.

• Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
• Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
• Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
• Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
• Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.

• Contributed to over 20 successful projects

• Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
• Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
• Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases

• Developed backend systems for the DWS Investment App, a white-label investment solution (robo-advisor), and an investment solution for institutional clients.
• Java 8-17, Kotlin, Spring Boot, Spring MVC, OpenAPI 3.0, JPA, JDBI, Oracle, Hazelcast, JXLS, Apache POI, Apache PDFBox, Apache Kafka & Avro, Active MQ, Elasticsearch, React Native, Spock Test, IntelliJ IDEA, Kubernetes, Helm, Microservices/Netflix-Stack, TeamCity, Splunk.
• Kanban team, continuous integration.
• Migrated existing applications from Deutsche Bank's private cloud environment to Azure as part of a carve-out.