
Amazon SQS Experts in Hamburg
to build resilient systems with vetted, available freelancersHire experts who design asynchronous workflows, integrate Amazon SQS with AWS Lambda and Amazon SNS, and improve queue reliability for distributed applications. Get fast, precise matching with vetted, available freelancers for your project.
Meet FRATCH Experts in Hamburg, who have recently used Amazon SQS
Niko S.
Last position:
Developing Architect, Technical Lead "gridlytics" at HH Energienetze
- Building a data integration platform for high, medium, and low voltage assets for contextual analysis of time series with master data from the SCADA control system (IEC 60870 104), INIS, and SAP.
- Responsibility for the architecture and implementation of the solution, as well as sparring partner for the Product Owner.
- Use of Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter, and various API gateways.
Thorsten B.
Last position:
Senior Backend Engineer at VTG Rail Europe
traigo is VTG's digital rail logistics and fleet management platform. It processes large volumes of telemetry, mileage, geofence, sensor and wagon-movement events in near real time and provides operational services for rail logistics customers across Europe.
As part of Team Customer Selfcare, I worked on the design, implementation, optimisation and operation of large-scale backend services and event-driven processing pipelines — covering both feature development and operational ownership of business-critical production systems. I also regularly acted as first responder for production incidents, data inconsistencies and performance investigations across multiple distributed services.
- Design and implementation of event-driven backend services.
- Migration and replacement of legacy processing pipelines.
- Development of replay / rebuild mechanisms for large event datasets.
- High-throughput asynchronous event processing on SNS / SQS.
- Database and query optimisation for PostgreSQL and DynamoDB.
- Design of scalable read / write models and aggregation pipelines.
- Production troubleshooting and operational support.
- Performance tuning and infrastructure scaling.
- Design and stabilisation of integration and system tests.
- Technical concepts, architecture documentation, and cross-team collaboration.
- Support the further development of existing GitLab CI/CD pipelines
Geofence & Wagon Stay Processing
- Algorithm to detect vehicles within geofences (entry, exit, dwell time).
- Event sourcing with guaranteed chronological order within the affected time window.
- Refactored geofence event and wagon-stay processing logic for performance.
- Resolved race conditions and event-ordering problems in distributed services; server-side filtering, aggregation and optimised query pipelines.
- Repair and replay tooling for corrupted or inconsistent movement data.
Fleet Metadata & Mileage
- Modernised the service; migrated storage from DynamoDB to PostgreSQL to improve traceability and accelerate new features.
- Scalable mileage aggregation and replay mechanisms.
- Read / write models and optimised queries for high-volume mileage calculations.
Sensor & Telematics Integration
- Integrated telemetry and sensor processing pipelines.
- Snapshot and state-calculation logic for sensor systems.
- APIs and persistence models for wagon sensor data; data-quality improvements.
- Further development of a service using gRPC for intra-service communication.
Movement Segment Processing & Routing
- Migrated services to new movement-segment event streams.
- Built replay and rebuild tooling for segment correction.
- Optimised throughput and reliability for high-volume event processing.
Condition Monitoring & Wagon Analytics
- APIs and backend services for wagon condition monitoring.
- Brake-wear prediction processing and wagon analytics functionality.
- PostgreSQL views and optimised query models for operational dashboards.
Operational Reliability - First Responder
- Investigated production incidents and distributed-system failures; DLQ analysis, replay and operational recovery.
- Tuned database performance and AWS infrastructure under production load.
- Improved observability, monitoring and operational tooling.
- Supported rollout strategies, monitoring and post-deployment stabilisation.
Rizwan B.
Last position:
Software Developer/Database/Devops at Sutor Bank
Project:
- Migration of existing VB6 applications to C# (Web API, web app)
- Report development and risk management systems (C#, API interfaces, databases)
- Document archive (API interfaces, databases)
Team size: 9 people
- Reports for Risk and Credit Management Development and maintenance of report structures to support risk and credit decisions, including data modeling, validation, and automated delivery for business departments.
- Migration and maintenance of a legacy system to the latest version of .NET for the asset management system Planning and execution of the modernization of an existing asset management system, including code refactoring, performance optimization, test automation, and sustainable maintenance after migration.
- Replacement of the COM-based archive connection with a REST API Redevelopment of the connection of the document archive (HYPARCHIV) to a REST API based on OpenAPI/Swagger, including archiving with index and stamp fields as well as PDF export into the customer portal.
- Redesign of payment receipt processing Replacement of an existing Oracle PL/SQL process with a new implementation in C# based on a business concept, including business alignment, data modeling, and test coverage.
- Design and implementation of tests, creation of deployment pipelines, and documentation
- Further development and implementation of change requests.
- Regular code reviews within the team as well as optimization of application scalability and stability
Technologies: C#, .NET 10, ASP.NET, Unit of Work, IoC, Three-Tier Architecture, Entity Framework Core, DB First, Web API, Swagger, OpenAPI, Python, Oracle, HYPARCHIV, Azure, PowerBI, DevOps, AKS (Azure Kubernetes Service), GIT, xUnit, NSubstitute, TypeScript, Vue.js, Pinia,
Methods: agile development using Scrum
Aiman R.
Last position:
Test Manager and Test Automation Engineer at Warehouse Management Company
- Introduced test management with SolMan
- Implemented test automation with TOSCA
- Analyzed, created, and automated test cases
- Built regression test portfolio
- Stakeholder meetings and alignments
- Financial management
Taher S.
Last position:
DevOps Engineer at Confidential
- Working with developers, security, and operations teams to align requirements
- Supporting product owners and development teams in using logging and monitoring solutions based on the Elastic Stack
- Developing and standardizing log schemas as well as defining practical standards for observability
- Designing and further developing logging architectures for complex, distributed multi-tenant environments
- Connecting application and infrastructure logs as well as security tools and metrics
- Optimizing data flows and modeling for analysis and reporting purposes
- Building automated infrastructures using Terraform/Terragrunt and Ansible
- Maintaining and further developing CI/CD pipelines in GitLab as well as automated development environments in Hetzner Robot
- Operating and automating Proxmox clusters including Ceph storage
- Setting up and operating Kubernetes (k3s) clusters on Fedora CoreOS including base services such as Vault, OpenLDAP, and HA Proxy
- Implementing security-critical infrastructures according to BSI baseline protection and securing existing systems
- Supporting the operation of solutions in cloud environments (including AWS)
- Working in agile teams using Scrum and Kanban
- Technologies/ applications: Elastic Stack (Elasticsearch, Logstash, Beats/Elastic Agent, Kibana), Terraform, Terragrunt, Ansible, GitLab CI/CD, GitOps, Proxmox, Proxmox Ceph, Kubernetes (k3s), OpenShift, Helm, Kustomize, Vault, OpenLDAP, HA Proxy, Hetzner Robot systems, AWS, Prometheus, Grafana, Syslog Linux/Windows, Docker, NGINX, Apache Security & Compliance (BSI baseline protection, SIEM/SOC)
Oliver L.
Last position:
Developer, Architect at libri GmbH
- Role: Developer, Architect
- Technologies: java, typescript, golang, spring (boot, web, security, data), Angular, AWS (OpenSearch, Aurora, SNS/SQS, CloudWatch, EC2, IAM), Kubernetes, Terraform, Helm, OAuth, Keycloak, CI/CD, gradlew, Liquibase, Test Driven Development, shell scripting
Florian F.
Last position:
Solution Architect with Developer Focus at SymFinIT Solutions GmbH
- Further development of a finance layer for subscription and one-time purchase billing and accounting.
- Technologies: Kotlin, AWS (SQS, S3, ElastiCache, Aurora), React, TypeScript, Coroutines, IntelliJ IDEA, Spring (Boot, Data, WebFlux), JUnit, Testcontainers, Cucumber, Liquibase, PostgreSQL, Webservices (REST), R2DBC, OpenAPI 3, Gradle, GIT, Docker, Netty, GitHub Actions, Jira/Confluence, arc42
Jürgen B.
Last position:
Software Developer at Inform AG
- Coaching junior developers
- Further development and customer-specific extensions of a standard software product (microservices (DDD) and partly monolith)
- Interface extensions
- Web services
- Test automation
- Design
- Technologies used: Java8, Java17, TypeScript, Python, PostgreSQL, Spring (Integration, Data, Boot), JPA, AWS (Cloud, Lambda, EC2, SQS/SNS), Microservices, Fitnesse/Cucumber, Gitlab
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
Mark P.
Last position:
Full-Stack Software Developer, Product Data Import at Otto (GmbH & Co KG)
- Manage and operate the product data import services for the Otto merchant
- Enhance and maintain the backend systems
- Optimize and maintain AWS infrastructure
- Build a new product data import API
- Design and plan stories and features
- Conduct code reviews to ensure code quality and best practices
- Analyze and fix bugs
- Technologies: Java, Spring Boot, Kafka, AWS, Fargate, Terraform, MongoDB, Mongo Atlas, OpenAPI, GitHub, GitHub Actions, GitHub Copilot, Akhq, Debezium, JUnit, Test Containers, Hexagonal Architecture
Christian H.
Last position:
Software Developer / Lead Developer at dpa (Deutsche Presse Agentur GmbH)
- Contributed to the development of the Rubix editorial system
- Implemented various microservices based on Java, AWS S3, AWS SQS, AWS SNS, and Spring Boot, deployed to AWS ECS and AWS Fargate
- Designed and developed AWS Lambdas using TypeScript
- Used PostgreSQL in an AWS RDS Aurora cluster and AWS DynamoDB
- Implemented continuous deployment with GitLab pipelines
- Built an Infrastructure as Code environment with AWS CDK
- Set up and maintained a monitoring platform using AWS CloudWatch
- Developed various frontend components with Vue.js
- Designed the microservice architecture applying Domain Driven Design and GraphQL interfaces
Lars K.
Last position:
Lead Drupal Developer at x-tention
- Lead Drupal 10 developer for several greenfield projects in the health sector
- Drupal architecture in a cloud environment
- Set up and maintain GitLab pipelines and Kustomize scripts for Kubernetes deployments
- Development of Docker images
- Developed custom Drupal modules for features such as OAuth and FHIR
- Drupal frontend theming using Bootstrap 5 and Single Directory Components
- Set up and maintain automated Playwright tests
Johannes E.
Last position:
Libri GmbH
- Operation and further development of the inventory system for booksellers (Quimus). It is an in-house development by Libri that is sold to customers as Software as a Service. The software is developed in an agile way by two developer teams (about 5 developers each). The software consists of around 25 Java microservices that mainly communicate via messaging and share a common Angular frontend. The application runs on Kubernetes in AWS.
- Technologies used: Java 17 & 21, Spring Boot 2 & 3, Hibernate, MySQL, Spring Cloud AWS, Lombok, AWS SQS, AWS SNS, AWS RDS, AWS S3, DynamoDB, Kubernetes, Docker, OpenSearch, Hibernate Search, Liquibase, Gradle, Terraform, Helm, GitLab CI, Keycloak OAuth2, TypeScript, Angular
- My focus until December 2023: Connecting additional POS systems to the inventory system. Connecting the data warehouse for report display. Extending existing features (goods receipts, invoicing, item management, ...). Operations and DevOps tasks.
- Focus from January 2024: Extracting the product search from the inventory system into a global service to use in other applications. Integrating the product search into the booksellers' online shops (also run by Libri). Importing and providing digital items in the product search.
René S.
Last position:
CRM Developer at CiS GmbH
- Developed a greenfield CRM for managing incoming customer requests for a municipal utility provider
- Implemented with PHP/Symfony 5, EasyAdmin, Doctrine ORM and Oracle XE
- Handed over to CiS GmbH after initial groundwork as planned
Sebastian W.
Last position:
Software Engineer & Consultant at Freelancer
Specialized in event driven microservice architecture in AWS with NodeJS, Typescript and Vue/React/Next in the frontend
Developed a SaaS product in the B2B sector
Used AWS services: DynamoDB, Lambda, SQS, SES, EventBridge, Cognito; Serverless-Framework; Rest-API
Implemented unit tests with Jest and Mocha
Set up CI/CD pipeline with GitHub Actions
Developed a SaaS product for organization management
Worked with AWS Microservice architecture and event driven design
Utilized CDK, NodeJS OpenAI-API, React, Vue
Continued use of DynamoDB, Lambda, SQS, SES, EventBridge, Cognito, Typescript
Maintained CI/CD pipeline with GitHub Actions
Discover over 15,000 top freelancers
Statistics of experts using Amazon SQS
Aggregated from the professional profiles of matched freelancers.
Experience
21 years (Germany: 19 years)

Position duration
1.9 years

Positions per freelancer
17 (Germany: 14)

Top business areas
Information Technology, Product Development, Quality Assurance

Top industries
Information Technology, Transportation, Retail

Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
55% (Germany: 87%)
Master's degree or higher
36% (Germany: 54%)
Doctorate
18% (Germany: 8%)

Certifications per freelancer
2 (Germany: 3)

Most common languages
German, English, French

Speak two or more languages
88% (Germany: 95%)
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 Hamburg 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 Hamburg using Amazon SQS
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 SQS 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 (100%)
- Transportation (69%)
- Retail (63%)
- Banking and Finance (56%)
- Healthcare (56%)
- Media and Entertainment (56%)
- Professional Services (50%)
- Energy (31%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Amazon SQS does
Amazon Simple Queue Service, commonly called Amazon SQS, is a fully managed message queuing service on AWS. It lets applications exchange messages without requiring every component to run at the same time. Companies use it to decouple services, absorb traffic peaks, and process work reliably in the background.
Queue patterns
Amazon SQS supports Standard queues for high-throughput workloads and FIFO queues when ordering and exactly-once processing requirements matter. Strong specialists choose visibility timeouts, delivery delays, retention settings, and dead-letter queues to match the business process. They also design idempotent consumers because messages can be delivered more than once.
AWS ecosystem
- Connect queues with AWS Lambda, Amazon SNS, and Amazon EventBridge
- Secure access with AWS Identity and Access Management and resource policies
- Monitor processing with Amazon CloudWatch metrics, logs, and alarms
- Provision infrastructure with AWS CloudFormation or Terraform
Professionals often combine SQS with container platforms, relational databases, NoSQL stores, and API services. They may also work with Amazon Simple Storage Service notifications, retry policies, and event-driven integration patterns.
Where it is used
Amazon SQS appears in order processing, payment workflows, media pipelines, customer notifications, data imports, and support automation. It is useful whenever a service should hand work to another component without waiting for immediate completion. Hamburg companies in logistics, commerce, manufacturing, and digital services may use it in systems that connect local operations with cloud workloads.
When to hire expertise
- Messages are lost, duplicated, delayed, or processed out of order
- Queue depth grows without clear scaling or alerting rules
- A monolith is being split into independently deployable services
- A migration needs secure, observable asynchronous communication
Freelance expertise helps when the queue is part of a critical workflow rather than a simple integration. A professional can review architecture, improve failure handling, define operational runbooks, and support remote or on-site collaboration in Hamburg according to the project’s needs.
What strong specialists deliver
A strong Amazon SQS specialist understands delivery semantics, concurrency, back-pressure, retries, and poison-message handling. They test failure scenarios instead of measuring only successful processing. Look for clear infrastructure definitions, useful dashboards, controlled permissions, documented message contracts, and integration tests that reflect real consumer behavior.
Frequently asked questions
Need clarity? These are the questions we hear most often about Amazon SQS.
Amazon SQS is used to move messages between application components without requiring them to run simultaneously. Companies use it for background jobs, order processing, notifications, data imports, and service-to-service integration.
Amazon SQS provides queues where consumers pull and process messages, while Amazon SNS primarily distributes notifications to subscribers. They are often combined when one event must reach several independent queues or services.
Amazon SQS FIFO queues suit workflows that require message ordering and controlled duplicate handling. Standard queues are usually a better fit when very high throughput and flexible processing matter more than strict ordering.
Amazon SQS work commonly involves AWS Lambda, Amazon SNS, IAM, CloudWatch, Terraform, CloudFormation, and container-based services. The specialist should also understand APIs, databases, distributed systems, observability, and failure recovery.
Amazon SQS can be straightforward for a basic queue, but critical workflows require deeper knowledge of retries, visibility timeouts, idempotency, dead-letter queues, and monitoring. Choose a specialist who has handled the same delivery and reliability risks your system faces.
Amazon SQS projects are well suited to remote collaboration because architecture, infrastructure, testing, and monitoring can be reviewed in shared repositories and cloud environments. For Hamburg teams, language expectations, on-site workshops, and working-hour overlap should be agreed before the engagement begins.
Amazon SQS quality is visible in documented message contracts, safe retry behavior, idempotent consumers, useful alarms, and tested failure paths. Ask the specialist to explain how the system handles duplicates, unavailable consumers, growing queue depth, and messages that cannot be processed.
Amazon SQS implementations often fail when teams ignore duplicate delivery, set unsuitable visibility timeouts, or rely on retries without a dead-letter strategy. Other warning signs include broad IAM permissions, missing queue-depth alerts, and consumers that cannot scale with incoming work.
The average hourly rate of freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects is 96 €, which corresponds to a daily rate of about 770 € based on an 8-hour working day.
Of the freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects, 55% hold at least a Bachelor's degree, 36% hold at least a Master's degree, and 18% hold a doctorate.
On average, freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects are German (100%), English (88%), and French (13%).
The most common industries among freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects are Information Technology (100%), Transportation (69%), and Retail (63%).
The most common business areas among freelancers in Hamburg, Germany who have used Amazon SQS in their recent projects are Information Technology (100%), Product Development (81%), and Quality Assurance (75%).
Main locations of FRATCH Experts, who have recently used Amazon SQS
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.
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