Amazon Athena Experts in Germany

I designed and developed an AI-powered multi-tenant platform on Azure that transforms SAP process recordings into technical documentation, presentations and automated tests, processing over 15,000 process recordings for enterprise customers like Würth. I owned the architecture, the production releases and the DevOps setup. I also designed a multi-tenant system with SSO and role-based access on Azure. Implemented an MCP Server with Dynamic OAuth Authentication.

Main Tasks:

• Sprint planning and feature preparation
• Design the multi-tenant platform architecture (FastAPI, SQLAlchemy, PostgreSQL row-level security for tenant isolation)
• Develop AI pipelines with Prefect for transcription (Azure Speech API), document generation and SAP screen-recording analysis (Claude, gpt-4-mini)
• Design and implement an MCP server to expose tenant knowledge to LLM clients (Claude), with async retrieval and reranking
• Implement LLM cost tracking, rate limiting and client pooling for Anthropic/OpenAI/Azure OpenAI endpoints
• Set up CI/CD: Docker images to Azure Container Registry, GitHub Actions, Azure Static Web Apps, Alembic migrations in containers
• Manage production releases and execute live data migrations for enterprise customers
• Define engineering standards and architecture patterns for the team

Environment: Azure / Azure Foundry / Python / FastAPI / Prefect / React / PostgreSQL

• Created a multi-agentic system supported by a knowledge graph to automate drafting of research papers
• Used multiple experts (OpenAI models) collaborating during document drafting
• Extracted useful information from the knowledge graph
• Technologies: LangChain, LangGraph, Smolagents, LlamaIndex, dspy
• Infrastructure: Terraform and GitHub Actions (CI/CD) on AWS
• Deployed initial application as a Streamlit app

• Developed & maintained customer analytical reporting solutions to identify revenue trends, performance drivers, risks & optimization opportunities to ensure data driven decision making across Sales, Finance, Product, Data Engineering & Controlling.
• Defined & analyzed customer trends & performance metrics to identify root causes behind variances, anomalies & emerging risks across business domains to deliver actionable recommendations.
• Developed & owned analytical data models & reporting layers to ensure scalability, performance & analytical robustness to support executive & operational reporting across business domains.
• Planned, tracked & executed projects by ensuring adherence to timelines, data accuracy, consistency, deliverables, reliability & data quality standards through rigorous validation & reconciliation processes.
• Raised the analytical maturity by formalizing analytical workflows, documenting data processes & standard operating procedures (SOPs) & conducting training sessions to drive adoption of self-service analytics & embed a data driven culture across operational and business teams.
• Took ownership of the end-to-end lifecycle roadmap from requirement gathering, collection, transformation, developing robust business logics to data storytelling & stakeholder delivery.
• Converted complexity into structured clarity by translating requirements & business processes into analytical recommendations to ensure alignment between non-technical & technical stakeholders.
• Conducted advanced SQL based analysis of complex business datasets to uncover trends, correlations & performance improvement opportunities.
• Drove process automation & efficiency improvements by leveraging Python, SQL optimization & AI assisted tools to reduce processing time & increase reliability across analytical & operational workflows.
• Standardized KPI definitions & reporting logic to ensure consistency & trust across reporting solutions.
• Developed process monitoring dashboards & analyses to identify inefficiencies, bottlenecks & compliance deviations across end-to-end business processes to derive actionable recommendations for process improvement & automation.

• Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
• Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
• Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
• Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.

• Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
• Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
• Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
• Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.

• Designed and developed interactive SAP Analytics Cloud (SAC) dashboards and reports for Finance, Supply Chain, Logistics, Procurement, HR, and Manufacturing, covering KPIs such as Profit & Loss, Balance Sheet, Fixed Costs, Headcount, Personnel Expenses, Stock Analysis, OTIF, Production Volume, BOM, Spend, and Compliance to Schedule.
• Built and optimized end-to-end ABAP CDS data models (Basic, Composite, and Consumption Views) using the VDM approach, integrating data from key SAP S/4HANA tables. Strong expertise in ABAP CDS, SQL, SAP data modeling,
• Collaborated with cross-functional teams to define KPI logic, standardized user story templates, resolved BI requests through JIRA, improved reporting performance, and delivered scalable, secure, and business-focused analytics solutions that enhanced decision-making and operational efficiency.
• Trained business stakeholders across various countries on SAP Analytics Cloud (SAC) dashboard usage and developed comprehensive training manuals to promote user adoption and enable self-service analytics.

• Extension and maintenance of the Doktree tax advisory document management tool
• Alfresco and Angular development
• Linux system maintenance

• Implementation of analytics and automation solutions for the Anti Financial Crime business unit
• Providing the infrastructure, including reusable data models and feature ingestion for production ML and rule based models in the areas of Account Take-Over and Card fraud detection, as well as Customer Risk Assessment
• Tools used: Snowflake, dbt, Looker, AWS, Python, Airflow, Metaflow

• Led end-to-end product discovery and strategy engagements for early-stage founders (pre-seed) clients, defining product vision, OKRs, and go-to-market strategies and roadmaps for their cloud-based and AI-enabled solutions.
• Designed scalable product operating models (Agile/Scrum, backlog governance, KPI frameworks) as part of the partnership, to improve delivery predictability and reduce feature cycle time by up to 30%.
• Built scalable product roadmaps aligned to fundraising milestones, helping founders articulate product vision, product<>market fit, and traction clearly to investors.

• Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
• Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
• Orchestrated pipelines with Azure Data Factory
• Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
• Led the Data Engineering team (3 members) in a functional role
• Conducted workshops to optimize and stabilize the data platform and the development process
• Collected and prioritized new requests, 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

• Built and operated an AWS Landing Zone with Terraform / OpenTofu (multi-account structure, IAM baselines, network and security standards)
• Designed and operated platform-oriented AWS architectures to standardize infrastructure and operations processes
• Built and operated Kubernetes-based platforms (EKS) as a shared runtime environment for application teams
• Established GitOps-based deployments with Argo CD and FluxCD
• Developed and operated central CI/CD platforms (GitLab CI, GitHub Actions, Jenkins)
• Enabled developer and project teams with reusable platform components
• Introduced and implemented FinOps structures (AWS Cost Explorer, CUR + Athena, Infracost, Grafana dashboards)
• Built and operated central observability platforms (Prometheus, Grafana, Loki, Alertmanager, CloudWatch)

• Led comprehensive AI workshops for professionals, focusing on AI-driven process automation.
• Tech Stack: n8n, Make, LLMs (OpenAI, Anthropic), Prompt Engineering, Process Mapping Tools.

Software solution company that offers tools for data-driven campaign management for Amazon Ads.

• From scratch, developed an insights tool for the Amazon DSP with several data pipelines to support reports
• Developed new backend features for the Ad Optimiser tool
• Developed and maintained data pipelines for the Ads reports
• Wrote unit tests and reviewed code from other developers
• Supported frontend developers and performed frontend development tasks