Amazon EventBridge Expert in Germany
to connect services faster with vetted, available specialistsHire experts who design event-driven architectures, connect SaaS applications and AWS services, and build reliable event routing with schemas, rules and targets. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Amazon EventBridge
Alexandru G.
Last position:
Principal Cloud DevOps Architect at BP
In my role as Senior Cloud DevOps Architect for BP, an oil and gas company, I had the mission to migrate the Electric Vehicle Charging platform of the EV Division from on-premises and Azure to AWS cloud, resulting in a hybrid multi-cloud, multi-tenant SaaS solution.
Deployment with Kubernetes for the application layer meant provisioning Kubernetes clusters managed by EKS and AKS, with a focus on integrating them into a multi-tenant environment. This integration was achieved by using Kubernetes namespaces and access controls to ensure data isolation and privacy enforcement.
In the database layer, we chose an RDS instance with PostgreSQL to support the backend infrastructure of our applications. Tenants shared the same RDS instance, but each had a dedicated schema.
To ingest near real-time data from physical charge points (CPOs), as IoT devices, via the OCPI protocol, we ran into significant delays with batch processing. As a result, we built a real-time streaming data pipeline using Apache Kafka, while prioritizing an event-driven architecture.
Led collaboration across multiple internal teams, external vendors, cloud providers, and on-site partners to integrate over five systems into a unified solution.
Achievements:
- Successfully designed and implemented hybrid multi-cloud solutions, integrating multiple cloud platforms (AWS, Azure) with on-premises infrastructure, using Site-to-Site VPNs, Firewalls, and Load Balancing.
- Led the migration of on-premises infrastructure to multi-cloud, multi-tenant infrastructure, resulting in 30% faster processing times.
- Migrated workloads from VMware and Hyper-V environments to cloud-based VMs, leveraging cloud-native services to optimize performance, cost efficiency, and scalability.
- Designed a multi-tenant Kubernetes platform leveraging the Kubernetes ecosystem, using Karpenter for dynamic EC2 node provisioning, KEDA for event-driven pod autoscaling (e.g., Kafka message lag), and Rancher for centralized monitoring of multiple clusters (EKS, AKS, or on-prem K8s), replacing Microsoft-centric Azure Arc management service.
- Designed and implemented Python-based FastAPI microservices as part of the EV core-backend on AWS EKS application layer, powering data ingestion and customer analytics pipelines.
- Developed asynchronous, event-driven APIs (Python-FastAPI) for real-time integration with CPOs, supporting OCPI 2.3 and OICP protocols.
- Designed and implemented a secure, production-grade Azure Databricks platform using Terraform, ensuring scalability and cost efficiency.
- Migrated on-premises ERP to a hybrid Dynamics 365 architecture with ERP hosted locally and CRM running in Azure, integrated via Azure Arc.
- Automated CI/CD pipelines for Databricks notebooks and jobs using GitHub Actions & Databricks CLI, reducing deployment time. Reduced infrastructure provisioning time by 70% by automating cloud resource deployment with GitOps.
- Ensured compliance with internal audit and data governance standards (GDPR) through OAuth2/OIDC-based authentication and fine-grained role-based access controls.
- Developed a Zero Trust security model, enforcing least-privilege access and microsegmentation, enhancing security posture and compliance with GDPR and NIST.
- Built interactive analytics dashboards in Amazon QuickSight, integrating data from S3 and Redshift to deliver real-time business insights and visualizations with embedded access for multi-tenant users.
- Led cloud security assessments and full-lifecycle cybersecurity integration during M&A, covering AWS, Azure, IAM (Entra ID), and data protection, while aligning security posture with NIST, ISO 27001, and GDPR across hybrid and cloud-native environments.
- Reduced cloud costs by 64% for a client's dev environment by implementing automated start/stop schedules for EC2 and RDS instances via AWS CDK with EventBridge Scheduler or AWS Systems Manager.
Tech stack:
- Infrastructure as Code: Terraform, AWS CDK, Ansible.
- Containers: Kubernetes on EKS, AKS, Docker.
- Streaming Data Processing: Kafka to Confluent Cloud, after AWS MSK.
- Frontend: TypeScript, React, NextJS, Hooks, Styled Components.
- Backend: Python with FastAPI, also Node.js with NestJS.
- Database: Aurora on PostgreSQL with TypeORM, RDS on SQL Server, Azure Databricks full setup and administration, ETL Pipelines.
- CI/CD and GitOps: GitHub Actions, Azure DevOps, ArgoCD.
- Monitoring and Observability: Prometheus and Grafana.
- Virtualization: Hyper-V, VMware Cloud on AWS, Azure Migrate.
- ERP Systems: Odoo, Microsoft Dynamics 365 Business Central on Azure, integrated with Azure Arc.
- Networking: Site-to-Site VPNs, AWS Direct Connect, Azure ExpressRoute, Firewalls (AWS Network Firewall, Azure Firewall).
- Security: IAM, NIST Framework, Zero Trust Security, AWS WAF, AWS Shield, GuardDuty.
Christof H.
Last position:
Senior Frontend Developer at HUK24 AG
- Designing new apps as well as enhancing and running 29 Angular apps for digital claims in an Nx monorepo
- Maintaining and improving a shared component library with ~300 libraries for multiple product teams
- Migrating all apps to a new design system including its component library and systematic refactoring
- Developing and maintaining the CI/CD pipelines (Jenkins, Azure DevOps, Terraform, AWS)
- Managing releases independently including branch handling, versioning, PR coordination and production deployment
- Implementing and maintaining tracking (Adobe Analytics)
- Ensuring accessibility according to BFSG/WCAG
- Test-driven development (TDD) with Jest and Cypress
- Code reviews, mentoring and setting up best practices in the team
- Technologies: TypeScript, Angular 16-20, RxJS, NgRx, Nx (Monorepo), npm, HTML, (S)CSS, Storybook, Jest, Cypress, Cucumber, Husky, Node.js, Git, AWS, Azure DevOps (Repos & Pipelines), Jenkins, Terraform, TDD, BFSG, WCAG, Nexus, IntelliJ, Adobe Analytics
Serge K.
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
Daniel B.
Last position:
Senior Cloud Consultant and Developer at SDIA/Leitmotiv
- Consulting an NGO in the field of data center sustainability in publicly funded projects (BMUKN with NADIKI and Umweltbundesamt with SIEC)
- Development of Python APIs and web applications, deployment on AWS/ECS with Terraform
- Collecting power consumption metrics for servers, CPUs, GPUs running AI workloads
- Technologies used: AWS, EC2, ECS, Fargate, CloudMap, VPC, Route53, Lambda, EventBridge, CodeBuild/CodePipeline/CodeDeploy, Terraform, Docker, Linux, Bash scripting, Python, Flask, SQLAlchemy, SQL, MariaDB, InfluxDB, Telegraf, Prometheus, Zabbix, Kubernetes, Letsencrypt, certificate management
Ulm P.
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Sara Z.
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 S.
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.
Jiri S.
Last position:
Quality Manager/Test Management at Noriba GmbH
- Test concept creation
- Creation of test processes
- Coordination of TC development: stress tests, functional tests, performance tests, high data rate tests, integration tests, etc.
- HW testing: FPGA, RF
- Test automation and regression tests
- Ensuring 24/7 operation of the test system
- Analysis & reporting
- Regular coordination of the test team, meetings with other stakeholders
- Communication and coordination with stakeholders and the project manager
Jan K.
Last position:
Software Architect: Training Platform for IT Career Changers at appvanced
- Mobile: Kotlin Multiplatform (KMP), Kotlin, Swift, SwiftUI, Jetpack Compose, Ktor, Room, Koin
- Backend: Spring Boot, GCP Cloud Run, GCP Load Balancer, GCP Eventarc
- Planned and developed a cloud backend architecture with Google Cloud Platform
- Developed a cross-platform architecture with Kotlin Multiplatform (KMP)
- Tech lead for comprehensive large project including webshop, two apps and omnichannel backend
Maziyar K.
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Alexey G.
Last position:
Cloud Architect & DevOps, Head of Architecture at ProSiebenSat.1 Digital GmbH / Seven.One Entertainment Group GmbH
- Co-authored enterprise cloud strategy including security and governance frameworks for 5 subsidiaries, and implemented part of the governance automation.
- Performed regular cloud cost optimization reviews across 10 teams resulting in ~20% cost reduction.
- Led the technology selection for the migration of in-house CIAM for 25M+ accounts to a SaaS solution, and worked with the product team through the migration.
- Supervised the technology selection and designed the architecture and delivery pipelines for the multi-tenant digital news and sports publishing platform, enabling ~250 editors within ~6 months of development start.
- Led the implementation of a multi-brand design system from idea and technical concept to implementation and rollout, enabling rapid UI prototyping for new products in a matter of hours.
- Managed a team of 4 architects and accelerated the professional growth of team members.
- Technologies: AWS cloud, Microservices, Docker, Python, Kafka, JavaScript, TypeScript, React.js, Node.js, GraphQL, REST, Gitlab CI, Visual Studio Code, git.
Andreas S.
Last position:
Lead Developer at Software
- Extended the document management system with a standard CMIS (Content Management Interoperability Services) interface
- Implemented CMIS core services like navigation, access rights, search, CRUD operations, and versioning in Java
- Implemented based on RESTful / OpenAPI services
- Delivered as a fat-jar and native container image
- Deployed on-premises and serverlessly as an Azure Container Application using Terraform
- Improved team autonomy through infrastructure engineering and short feedback loops
- Established observability with OpenTelemetry, Azure Monitor, and Azure Logic Apps
- Introduced Terraform and trunk-based development processes
- Ensured quality with BDD tests in C# using SpecFlow and Testcontainers
- Created Azure DevOps pipeline integration tests
- Introduced cloud deployment processes
- Trained staff in cloud and Terraform
Alexis P.
Last position:
Freelance Team Lead Backend Applications E-Commerce at The Quality Group GmbH
- Building and maintaining an event-driven microservice architecture around Shopify
- Documenting with Confluence and IcePanel (C4)
- Using PHP 8.2, Symfony, Shopify, Bref, AWS, SQS, EventBridge, Cloud, DevOps, Datadog, Docker, Kubernetes, Jira, GitHub, Scrum, Kanban, PHPUnit, Prophecy and Swagger
Pappu P.
Last position:
Senior Cloud Consultant (AWS Services and Consulting) at devoteam GmbH
- Developed automated ETL pipelines with AWS Glue and Athena to ensure consistent data quality and governance requirements
- Implemented validation, anonymization, and encryption measures for data in compliance with GDPR
- Optimized cloud costs by introducing FinOps practices and increased transparency for business units
- Monitored performance, performed root cause analyses, and ensured adherence to SLAs
- Supported data and solution architects in building scalable data models for ML and analytics scenarios
Amit G.
Last position:
Authorized Officer - Software Engineer at UBS
- Built a fee proposal tool automating financial advisor fee calculations, reducing manual processing from hours to seconds.
- Developed Spring Boot microservices with REST APIs on Azure SQL, replacing mainframe procedures, improving latency by 60%.
- Migrated Tomcat applications from on-premises RHEL servers to Azure Kubernetes Service (AKS).
- Automated testing and deployment processes using CI/CD pipelines in GitLab, reducing deployment time by 90%.
- Streamlined recurring reporting workflows by automating report generation using Spring Batch.
Discover over 15,000 top freelancers
Statistics of experts using Amazon EventBridge
Aggregated from the professional profiles of matched freelancers.
Experience
19 years
Position duration
2 years
Positions per freelancer
13
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Media and Entertainment, Retail
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
86%
Master's degree or higher
57%
Doctorate
7%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using Amazon EventBridge
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Amazon EventBridge experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (94%)
- Media and Entertainment (61%)
- Retail (56%)
- Education (50%)
- Banking and Finance (39%)
- Professional Services (39%)
- Energy (33%)
- Healthcare (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Event-driven foundation
Amazon EventBridge is a serverless event bus for connecting applications, AWS services and external software through events. It routes state changes and business signals to targets without requiring tightly coupled service integrations. Teams use it for automation, notifications, workflows and distributed systems.
Core capabilities
Experts configure event buses, event patterns, rules and targets for reliable routing. They work with custom events, AWS service events and partner integrations, while applying input transformation, filtering and retry behaviour. Schema discovery and registries help teams understand and reuse event contracts.
AWS ecosystem
EventBridge projects often connect Lambda, Step Functions, SQS, SNS, API destinations and CloudWatch. Strong professionals also understand IAM, KMS, CloudFormation or Terraform, observability and dead-letter queues. They may integrate Salesforce, SaaS APIs or private services through secure network and authentication designs.
Typical project work
- Replace point-to-point integrations with event-based routing
- Create rules that trigger serverless workflows and operational alerts
- Connect AWS accounts, regions, partners and SaaS applications
- Define schemas, version event contracts and document ownership
- Test retries, failures, permissions and duplicate event handling
When expertise matters
Companies bring in freelance specialists when an integration landscape is growing difficult to maintain or when a new product needs asynchronous workflows. German teams may value professionals who can work remotely across time zones or join on-site discovery sessions, with clear documentation in English or German. Specialist support is also useful during migrations, incident reviews and delivery handovers.
What quality looks like
A strong professional designs events around stable business facts rather than internal implementation details. They plan for at-least-once delivery, idempotency, ordering limits, replay, monitoring and controlled access. They explain trade-offs against direct APIs, SNS or Kafka, keep infrastructure reproducible, and leave teams with tested rules and useful runbooks.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Amazon EventBridge.
Amazon EventBridge is used to route events between AWS services, applications, SaaS products and custom systems. Companies use it for serverless workflows, automation, notifications, integration flows and loosely coupled architectures.
Amazon EventBridge focuses on event routing with filtering, rules, schemas and integrations, while SNS is commonly used for publish-subscribe fan-out and SQS for durable queue processing. Kafka is often chosen for high-throughput streaming, retention and detailed consumer control. The right choice depends on delivery guarantees, event volume, replay needs and operational ownership.
A strong Amazon EventBridge specialist usually understands Lambda, Step Functions, SQS, SNS, IAM, CloudWatch and infrastructure as code. Experience with API design, JSON schemas, idempotency, observability and secure SaaS integrations is also valuable.
For a small routing change, a specialist who understands AWS event patterns and permissions may be sufficient. Larger migrations or multi-account architectures require proven experience with event contracts, failure handling, monitoring and operational handover. Ask for examples that resemble your integration landscape rather than relying only on credentials.
Amazon EventBridge is well suited to remote collaboration because its configuration, infrastructure and event contracts can be reviewed in shared repositories. Teams in Germany should agree on working hours, documentation language, access procedures and incident responsibilities before implementation. On-site workshops can still help with discovery and domain alignment.
Ask how the specialist handles duplicate events, retries, dead-letter queues, schema changes, permissions and observability. A capable Amazon EventBridge freelancer should explain trade-offs clearly, show how rules are tested, and provide infrastructure definitions and runbooks rather than only a working demonstration.
Amazon EventBridge can reduce direct dependencies when systems communicate through business events, but it does not replace every API. Synchronous queries, immediate validation and command-style interactions may still need APIs. A sound design combines both patterns and makes ownership and failure behaviour explicit.
Before starting with Amazon EventBridge, freelancers should clarify event ownership, source systems, target actions, data sensitivity, delivery expectations and deployment practices. They should also confirm account boundaries, network access, alerting, replay requirements and how the client will operate the solution after handover.
The average hourly rate of freelancers in Germany who have used Amazon EventBridge in their recent projects is 107 €, which corresponds to a daily rate of about 855 € based on an 8-hour working day.
Of the freelancers in Germany who have used Amazon EventBridge in their recent projects, 86% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 7% hold a doctorate.
On average, freelancers in Germany who have used Amazon EventBridge in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Germany who have used Amazon EventBridge in their recent projects are German (100%), English (100%), and French (22%).
The most common industries among freelancers in Germany who have used Amazon EventBridge in their recent projects are Information Technology (94%), Media and Entertainment (61%), and Retail (56%).
The most common business areas among freelancers in Germany who have used Amazon EventBridge in their recent projects are Information Technology (100%), Product Development (83%), and Business Intelligence (67%).
Main locations of FRATCH Experts, who have recently used Amazon EventBridge
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
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Philipp Thomaschewski
FRATCH CEO
