AWS IoT Core Experts in Germany
in minutes with vetted specialists and the power of AIHire experts who design secure device connectivity, MQTT message flows, and rules-based data routing in AWS IoT Core. They also handle device fleets, certificates, and integrations with AWS services, with fast and precise matching to vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used AWS IoT Core
Michael Fecher
Last position:
Freelancer, Solution Architect at Schufa AG
- Helped to design the AWS infrastructure, integrated services and backend architecture for use cases of an on-premise solution and partial migrations to AWS with fast response times
- Implemented automated AWS integration test suites
- Implemented mission-critical components and delivered them before the deadline in a production-ready state with operation and monitoring concepts
- This 2-month subproject was about building a data-intense pipeline (5 TB) to be enriched continuously with data
- Designed and implemented reusable AWS CDK constructs to be used across the company’s teams to enable faster onboarding with AWS
- Coached on AWS topics, distributed software patterns, security, domain-driven design, agile collaboration and documentation to improve performance and collaboration
- Technologies: AWS, GitHub Actions, ETL, monitoring, operations, TypeScript, Python, AWS CDK, CloudFormation, Java, Docker, AWS ECS, AWS Lambda, serverless, Jenkins, DevOps principles
Clemens Berlin
Last position:
Director of Engineering at SIDES GmbH
- Leading engineering organization of 45 engineers across 8 teams while serving dual role as Head of Backend
- Addressed critical organizational challenges including siloed departments, lack of engineering processes, and absence of technical strategy
- Executed comprehensive engineering leadership in people management, organizational design, and strategic planning
- Drove platform modernization including migration to a new Python backend, implementation of React micro-frontends, and transition to event-driven architecture
- Established engineering excellence framework through Architecture Decision Records, RFC processes, and comprehensive technology roadmapping
- Transformed engineering into integrated business partner by building collaboration channels with Product Management and Customer Operations teams
- Reduced escaped bugs by 50% and increased test coverage in legacy systems
- Achieved 100% Q2 roadmap delivery through realistic planning and improved estimation accuracy
- Introduced AI engineering strategy, establishing policies, providing tools, and training team on prompt engineering and agentic workflows
- Saved €10k monthly through infrastructure optimization including AWS IoT to RabbitMQ migration and decommissioning legacy systems
- Improved team engagement from 60% to 100% survey participation and enhanced eNPS scores among team leaders
- Built high-performance team through strategic hiring of Python, Go, and frontend engineers and improved onboarding
- Implementing transition to self-organized cross-functional teams
Arne Hendricks
Last position:
Embedded Fullstack Developer at IoT / Infrastructure Automation Sector
- Analysis of legacy codebase and identification of architectural issues, implementing improvements in coordination with the Product Owner.
- Development of clean, efficient, and fully documented code following established software engineering practices and standards.
- Analysis of Erlang components in backend and device layers to provide recommendations for ensuring stable system operation.
- Setup and optimization of CI/CD pipelines on client infrastructure, including testing, debugging, and certificate management quality assurance.
- Participation in planning, design, and implementation of epics and stories according to Product Owner specifications.
- Technical consultation for Product Owner regarding Erlang codebase management and best practices.
- Collaboration with Product Owner, Scrum Master, and development team to ensure timely delivery of features.
- Elixir & Phoenix + PostgreSQL
- Erlang
- IoT
- CI/CD
- Git
- Agile/Scrum
- Docker
- Kubernetes
- Frontend (VueJS)
- Embedded Devices
Meenakumar Vaikundam
Last position:
Senior Embedded Technical Manager at IIT Madras Pravartak Technologies
- Led 14 member dev team and delivered postgresql database integration and performance optimization
- Delivered 8 K lines of C code with fewer defects (5 medium to low) in 8 months of development
- Integrate open source pgVector for AI application of the database for exact and nearest neighbor search
Volker Krause
Last position:
Head of Engineering at Infoniqa
- Led engineering execution: roadmap planning, capacity alignment, risk management, dependencies, and delivery tracking.
- Consolidated multiple payroll product lines into a unified SaaS platform on Dynamics 365 Business Central, enabling scalable post-merger operations and reducing operational complexity across the portfolio.
- Restructured engineering and product teams in a remote-first setting across Germany, Austria and Poland, consisting of five cross-functional units: compliance/enabling, platform, DevOps and two stream-aligned teams with total FTE depending on phase of reorganisation.
- Rebuilt the mid-level leadership layer and mentored engineering leaders, establishing a leadership pipeline and strengthening architectural decision-making across teams for scalable growth, delivery ownership and predictability.
- Designed platform foundations and system boundaries using Team Topologies aligned structures, enabling scalable ownership, clear interfaces and parallel development across distributed teams.
- Spearheaded AI transformation by implementing AI-assisted SDLC practices using SpecKit and GitHub Actions for automated, executable specifications, while delivering agentic product capabilities by securely exposing platform data and services to AI agents and copilots via RAG-based retrieval pipelines and MCP-style extensions.
- Drove modularisation of tightly coupled legacy logic into independently deployable services, improving maintainability, testability and architectural clarity while preserving continuity through targeted, low-risk extraction rather than full rewrites.
- Established observability, CI/CD and DevOps governance as platform capabilities, increasing automated compliance gates from 25% to 75% and improving deployment cadence by 40% across 15+ product versions.
- Improved operational resilience using DORA-aligned practices (lead time ↓50%, SaaS MTTR ↓85%), strengthening reliability and reducing support overhead.
- Coordinated engineering recovery for the German payroll platform during a company-wide P0 ransomware incident; restored platform continuity within 72h, validated data integrity, and rolled out hardened runbooks and automated recovery playbooks.
- Responsible for budget compliance and cost oversight in Engineering, with limited P&L responsibility and participating in the annual COGS/OPEX/CAPEX planning cycle.
Hanno Kolvenbach
Last position:
Vice President, Product Development at EdgeIQ, Inc
- Responsible for EdgeIQ Symphony, a low-code workflow orchestration platform for the Connected Product Economy
- Developed an IoT platform that can scale to millions of devices and billions of processed events
- Flexible platform design allows management of heterogeneous device fleets
- Integration with modern IoT technologies like MQTT, LWM2M, x509 certificate-based authentication, TPM2.0-hardware encryption
Ankit Agrawal
Last position:
Staff Engineer at Shopify Financial Services
- Took charge as a main Tech Lead within a dynamic team of 10 professionals within Shopify Capital
- Played a pivotal role in conceiving and shaping novel product concepts, crafted comprehensive feasibility assessments, devised strategic roadmaps, and meticulously evaluated associated risks
- Innovatively devised a transformative project that streamlined the manual verification process of Capital AU, resulted in a remarkable 25% reduction in manual intervention
- Delivered comprehensive product consultation, intricate technical design, and seamless implementation strategies for Shopify Capital across diverse international markets
- Orchestrated effective collaboration across multifunctional teams, fostered creation of the groundbreaking solutions that empowered enterprises to seamlessly access essential capital, fueled their expansion and advancement
- Demonstrated a history of delivering top-tier solutions that align with business goals and surpass customer expectations
Janusz Mazurek
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Discover over 15,000 top freelancers
Statistics of experts using AWS IoT Core
Aggregated from the professional profiles of matched freelancers.
Experience
21 years
Position duration
2.8 years
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Business Intelligence, Quality Assurance
Bachelor's degree or higher
88%
Master's degree or higher
75%
Certifications per freelancer
2
Most common languages
German, English, Dutch
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 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 AWS IoT Core
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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Device connectivity
AWS IoT Core is the managed AWS service for connecting devices to the cloud. It is used to send telemetry, receive commands, and keep device fleets in sync through MQTT, HTTPS, and WebSockets. Strong experts know how to shape message topics, access control, and device identity so data moves cleanly.
Security and access
A good setup starts with certificates, policies, and device authentication. Specialists work with mutual TLS, the AWS IoT Device Shadow, and certificate rotation to keep connections stable and controlled. They also design topic permissions so devices only publish and subscribe where they should.
Data routing
- Define rules that forward messages to AWS Lambda, Amazon S3, Amazon DynamoDB, or Amazon Kinesis
- Filter noisy device data before it reaches downstream systems
- Map telemetry into formats that analytics and operations teams can use
- Add retry and error handling for reliable event delivery
This is where AWS IoT Core often connects with wider AWS architectures. Experts help make the flow from edge devices to storage, processing, and alerts predictable.
Common projects
Companies bring in freelance specialists for fleet onboarding, proof-of-concept builds, device shadow design, and incident fixes. In Germany, this often fits industrial IoT, energy systems, logistics, and connected products where remote collaboration is normal but plant or device access may require on-site work.
Ecosystem skills
Strong professionals usually know more than the core service itself. They work with IoT SDKs, AWS Lambda, IAM, CloudWatch, Greengrass, and certificate management, and they understand how to troubleshoot disconnects, latency, and payload issues. Clear documentation and careful testing matter as much as code.
What strong experts deliver
- Secure device registration and onboarding
- Topic design and message flow planning
- Rules engine integration with AWS services
- Monitoring, logging, and operational handover
- Support for scaling from pilot to production
The best AWS IoT Core specialists keep the architecture simple enough to run and strict enough to secure. They leave behind clear topic models, IAM decisions, and runbooks that teams can maintain.
Frequently asked questions
Key details about AWS IoT Core, drawn from the questions we get asked most.
AWS IoT Core is used to connect devices, sensors, gateways, and connected products to AWS. Companies use it for telemetry ingestion, command delivery, device shadows, and routing messages into storage, analytics, or alerting workflows.
AWS IoT Core focuses on secure cloud connectivity and message handling. AWS IoT Greengrass adds edge-side logic, local processing, and offline continuity, so the two are often used together rather than treated as substitutes.
Bring in a freelancer when you need a clean device onboarding flow, a new message model, a production fix, or help connecting devices to other AWS services. AWS IoT Core projects often need someone who has already solved certificate, topic, and routing problems in real systems.
A strong AWS IoT Core specialist usually knows MQTT, IAM, Lambda, CloudWatch, device certificates, and basic edge concepts. Knowledge of DynamoDB, S3, Kinesis, and Greengrass is also useful when device data needs to move beyond simple messaging.
Most AWS IoT Core work benefits from someone who has handled security, routing, and operations, not just a quick proof of concept. If the project involves many devices, strict access rules, or production monitoring, look for a specialist who can design the full flow.
Yes. AWS IoT Core work is often remote because most tasks are design, configuration, testing, and cloud integration. On-site time in Germany can still help when teams need access to hardware, factory networks, or lab equipment.
Look for clear topic naming, secure certificate handling, solid IAM design, and a simple rules engine setup. A strong AWS IoT Core expert can explain how messages move, how failures are handled, and how the system will be monitored after handover.
They often start with unstable device connections, unclear payload formats, and insecure access rules. AWS IoT Core specialists also clean up message routing so telemetry reaches the right AWS service without brittle custom code.
The average hourly rate of freelancers in Germany who have used AWS IoT Core in their recent projects is 123 €, which corresponds to a daily rate of about 985 € based on an 8-hour working day.
Of the freelancers in Germany who have used AWS IoT Core in their recent projects, 88% hold at least a Bachelor's degree and 75% hold at least a Master's degree.
On average, freelancers in Germany who have used AWS IoT Core in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Germany who have used AWS IoT Core in their recent projects are German (100%), English (100%), and Dutch (13%).
The most common industries among freelancers in Germany who have used AWS IoT Core in their recent projects are Information Technology (100%), Banking and Finance (63%), and Automotive (38%).
The most common business areas among freelancers in Germany who have used AWS IoT Core in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (88%).
Main locations of FRATCH Experts, who have recently used AWS IoT Core
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
