Amazon S3 Experts in Munich

Michael Nelz

Senior ML Engineer | AI Engineer | Problem Solver

Eichenau

Last position:

Senior ML Engineer, AI Engineer at Lanxess AG

Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.

Mohamad Dib-Skhni

DevOps Engineer & IT-Security-Architect

Last position:

DevOps Engineer & IT-Security-Architect at BMW Group

Set up Azure Kubernetes clusters (AKS) with network policies, security groups, and RBAC
Developed Terraform-based infrastructure as code for secure, reproducible deployments in the BMW Azure cloud
Hardened CI/CD pipelines using Jenkins, SonarQube, Fortify SSC, and Contrast AST
Integrated SAP BTP/Kyma and ServiceNow GRC

Serge Kalinin

MLOps (machine learning operations)

Last position:

MLOps (machine learning operations) at REWE Digital GmbH

It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment

Anitha Namineni

Senior Data Engineer

München

Last position:

Senior Data Engineer at Accenture GmbH

Designed, developed, and configured scalable data applications aligned with business processes and technical requirements.
Architected scalable, cost-effective data architectures leveraging Snowflake across AWS, Azure and GCP, integrating dbt for data transformation and modeling.
Built and maintained robust ETL Data Pipelines, ensuring high data quality for seamless migration and cross-system integration.
Demonstrated strong expertise in SQL & Python with extensive experience in data modeling, ETL/ELT pipeline development, and streaming data processing; proficient in Git-based version control, CI/CD practices, and testing frameworks, with solid knowledge of data quality, observability, cost optimization, security, and data governance principles.
Led multiple data migration initiatives from SAP HANA to Snowflake using a modular dbt framework.
Designed and maintained end-to-end data transformation workflows using dbt on Snowflake, implemented layered data models, optimized performance, and ensured high-quality data delivery for business intelligence and reporting.
Managed development, QA, and production deployments through structured version control and release management using GitLab.
Integrated and centralized data from multiple sources including relational databases, flat files, Excel, and large-scale systems into Snowflake.
Applied strong expertise in Sales, Marketing, HR, and ERP data domains, developing and maintaining relevant KPIs and reporting solutions.
Collaborated with cross-functional teams to deliver end-to-end data solutions on schedule through proactive issue resolution and effective coordination.
Administered the Snowflake sandbox environment for Data Engineering division.
Trained colleagues transitioning into data roles on Snowflake and provided technical guidance and mentorship to junior team members.

Hardeep Bhutter

Sr. Data Engineer

Last position:

Sr. Data Engineer at Charles Schwab Bank

Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
Created and maintained dashboards in Power BI to provide actionable insights.

Vitaliy Ryumshyn

DevOps GitOps (temp)

Puchheim

Last position:

DevOps GitOps (temp) at Signal Iduna

Responsible for Openshift/Kubernetes on-prem administration and developer support.
Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.

Sara Zarei

Data Analyst / Analytics Engineer

Last position:

Data Analyst / Analytics Engineer at IDG Tech Media GmbH

Designed, built, and maintained scalable ETL/ELT data pipelines using Python, SQL, REST APIs, AWS Lambda, S3, PostgreSQL RDS, EventBridge, CloudWatch, Docker, Apache Airflow, and BigQuery – integrating data from GA4, Google Ads, Meta Ads, CMS, CRM, newsletters, events, and B2C ordering systems into analytics-ready datasets.
Built a cross-brand lakehouse architecture from AWS to BigQuery – transforming raw JSON/CSV data into structured, partitioned, and reusable reporting layers with staging, intermediate, canonical, and mart models.
Designed relational and dimensional data models: 3NF staging models, star schemas, fact tables, dimension tables, daily KPI aggregates, and dashboard-optimized marts for marketing, content, subscription, event, CRM, and revenue analysis.
Implemented production-grade data quality and pipeline reliability features: incremental loads, idempotent upserts, deduplication, schema validation, row matching, null checks, anomaly detection, freshness monitoring, logging, retries, and error alerts.
Automated cross-brand reporting processes and data products – pipelines for 73 newsletter campaigns, 31 lead list syncs, 52 event partner reports, and a 500K-record company matching pipeline; reduced manual data preparation by approx. 70% and increased analyst productivity by approx. 30%.

Christian Schulz

Data-Scientist/AI Engineer

Ismaning

Last position:

Data-Scientist/AI Engineer at The Marcom Engine GmbH & Co. KG

Concept creation and implementing AI Agents in AWS Cloud
Continuously alignment with stakeholders
Collaborate with DevOps
Technologies: Git, CI/CD (GitHub Actions), Python/ML, Streamlit, Deno/typescript, AWS SAM, AWS Bedrock, AWS Lambda, AWS Dynamo DB, AWS S3, AWS Event Bridge etc.

Roxana Girdu

Freelance Senior Frontend Developer

Last position:

Freelance Senior Frontend Developer at RHI Magnesita

Designed and developed a high-performance internal resource management platform using React and TypeScript, optimizing dynamic data rendering and state management.
Built a React Native application to support mobile access to internal tools, enabling on-the-go project tracking for field teams.
Developed custom 2D canvas-based visualizations using Pixi.js to simulate material flows and refractory layer behaviors.
Integrated Pixi.js with React components for interactive diagrams and real-time UI updates.
Developed interactive 3D visualizations using React.js for displaying refractory product layouts and simulations, supporting engineering and sales teams with dynamic product previews.
Integrated Three.js within the React ecosystem to allow manipulation of 3D models in real-time via browser, enhancing user engagement and field configurability.
Integrated a headless CMS to enable dynamic content updates by non-technical users, reducing content deployment time by 40%.
Led AWS CloudFront optimization initiatives, improving portal load speeds by 30% globally.
Actively collaborated with cross-functional Agile teams and product owners to deliver prioritized features with a fast feedback loop.
Key Technologies: React.js, React Native, Three.js, TypeScript, Contentful CMS, AWS S3/Lambda/CloudFront, Cypress, Agile Scrum

Jennifer Kiunke

AI Product Manager and Engineer

Last position:

AI Product Manager and Engineer at Human-in-the-Loop Studio

Architected and built a GenAI-based automated asset-generation tool for social media campaigns using Nano Banana and Python. It takes a campaign brief, target audience, and two products as input, generates optimized prompts for image and text creation, and uses functions for text positioning, visually appealing overlays, resizing, and structured uploads to AWS S3.
Engineered and built a multi-agent news intelligence platform with specialized roles including retriever agents (Tavily web scraping), synthesizer agents, and Claude as curator/orchestrator, designing autonomous agent collaboration patterns using LangChain and RAG.
Built an autonomous customer service agent using n8n and LLMs, delivering end-to-end support automation with transparent reasoning, governance controls, and scalable workflow orchestration using Python and vector databases.
Developed a financial validation engine featuring ML-powered anomaly detection for invoice plausibility, compliance automation, and risk mitigation using TensorFlow and SQL.
Created a cost optimization application using OCR, AI, Pandas, and NumPy for data analysis to identify cost optimization potential.

Clarissa Heinemann

Data & Automation Engineer | M.Sc. Information Systems

Last position:

AI Trainer at Komdis GmbH

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

Ales Loncar

Senior DevOps Consultant (Freelance)

Last position:

Senior DevOps Consultant (Freelance) at European Union Agency (via IBM)

Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.

Stephan Sahm

Senior Data/ML Consultant & Technical Lead

München

Last position:

Senior Data/ML Consultant & Technical Lead at Jolin.io

Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)

Alexandru Gunescu

Head of Cloud Infrastructure

Last position:

Head of Cloud Infrastructure at BP

Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
Supported development and maintenance of IT strategy aligned with business requirements
Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
Developed a two-year infrastructure technology roadmap yielding 25% cost savings
Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics

Nikolay Tonev