Amazon Redshift Experts in Berlin

Led FP&A tech transformation for a 9-figure business – from resolving legacy technical debt to leading AI-native EPM implementation

• Driving end-to-end FP&A transformation, from architecture redesign through EPM tool selection to rollout
• Ran evaluation of 12+ EPM platforms, from vendor negotiation to selection framework tied to long-term planning
• Diagnosed constraints in financial planning architecture, presented findings to the CFO, and secured executive mandate to redesign FP&A infrastructure from the ground up

• Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
• Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
• Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
• Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
• Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
• Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
• Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
• Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
• Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
• Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

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.

• Fractional leadership; consulting growth-stage startups and scale-ups on data strategy, ML products, and platform foundations
• Building decisioning systems for growth, personalization, & product experimentation, across e-Commerce, Digital Health, Energy, and Logistics
• Exploring Agentic AI & LLM-based tooling for production readiness patterns

• Analysis of complex business processes and end-to-end user journeys in digital product and platform environments
• Gathering, structuring, and prioritizing business and technical requirements (Functional / Non-Functional Requirements)
• Translating business goals into actionable requirements, user stories, and acceptance criteria
• Conducting stakeholder interviews, workshops, and reviews with business teams, IT, UX, and management
• Creating and maintaining requirement artifacts (BRD, FRD, user stories, process models, decision papers)
• Ensuring consistency between business needs, technical implementation, and product vision
• Close collaboration with development teams to clarify business questions during implementation
• Support with impact analyses (A/B tests), change requests, and scope management
• Quality assurance of implemented requirements including acceptance criteria and business testing
• Advising on the further development of product strategy and roadmap structure
• Prioritizing backlog items based on business value
• Defining and sharpening product goals, KPIs, MVP definition, and other success metrics
• Evaluating new features, tools, and initiatives from a user and business perspective
• Facilitating decision-making between business, product, and technology
• Supporting go-to-market considerations and product positioning
• Sparring partner for product and stakeholder decisions at management level
• Dashboard creation, data modeling, BI report administration, and data analysis in Power BI

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

• Assessment of the existing reporting landscape and strategic bundling of needs
• Migration and consolidation of reports to Metabase, connected to ClickHouse as the data foundation
• Building and maintaining data pipelines

Stack: Metabase · ClickHouse · Appsmith · Airflow

• Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
• Work with customers to understand their challenges and provide the best solutions based on open-source data products
• Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
• Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
• Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
• Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
• Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
• Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible

• Own strategy and roadmap for the payment orchestration and risk intelligence products serving enterprise subscription customers.
• Conduct deep workflow discovery and user interviews to redesign onboarding experience, resulting in 5× funnel throughput and 70% reduction in manual steps.
• Define PRDs for scalable data pipelines, fraud signals, and automation logic, improving insight accuracy and speed of decision-making by 30%.
• Partner with engineering, data, design, and security to ship 15+ enterprise features with 100% successful release quality.
• Introduce risk analytics dashboards and performance KPIs, reducing investigation time by 40% and improving visibility across teams.
• Lead prioritization of new capabilities, tech debt, and security initiatives (PCI DSS, access controls, auditability).
• Lead development of ML-based fraud detection models (regression, decision trees) to identify high-risk transactions, reducing chargebacks by 20%.
• Design end-to-end analytics dashboards (Tableau, Redshift) to visualise global risk exposure, cutting onboarding SLA from 2.4 days to 3 minutes.
• Partner with engineering and data teams to deploy scalable payment risk frameworks, enhancing compliance visibility and decision speed.
• Mentor analysts and data scientists through agile sprint cycles, embedding a data-driven culture across risk operations.

• Performed qualitative and quantitative analysis of extracted findings, categorizing themes, evaluating methodologies, and assessing study quality and reliability.
• Produced research reports and evidence summaries communicating key trends, gaps, and opportunities to academic advisors or cross-functional teams.
• Presented findings through well-structured visualizations, tables, and narrative summaries to support decision-making and guide future research directions.

• Matched light and mood to the plates
• Self-motivated, with a strong sense of personal responsibility
• Learned and adapted quickly to new technology and software applications
• Used strong analytical and problem-solving skills to develop effective solutions for challenging situations
• Excellent communication skills, both verbal and written
• Identified issues, analyzed information and provided solutions to problems
• Worked flexible hours across night, weekend, and holiday shifts

• 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.

• Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
• Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
• Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
• Contributed to hiring and technical interviews as part of the recruitment panel.