Amazon Kinesis Experts in Munich
matched in minutesHire experts who design streaming architectures, connect Kinesis Data Streams with AWS analytics services, and deliver event-driven data pipelines for production systems. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Amazon Kinesis
Paul W.
Last position:
Enterprise Architect at ePrimo GmbH
Led the end-to-end integration and migration architecture for decommissioning SAP IS-U market communication and transitioning to Salesforce Marketing Cloud (SFMC) with E.ON IT Services — covering regulated EDIFACT market messaging, a three-phase data migration (transfer of market message inventory after cutover), redesign of market communication processes, and full GDPR and German energy-market compliance.
- Designed the three-tier target architecture (SAP IS-U → NScale B2B gateway → SFMC) processing 50,000–100,000 EDIFACT messages daily within sub-5-minute SLAs.
- Architected the three-phase data migration: 36 months of historical data, zero-loss cutover of in-flight market messages, and near-real-time CDC synchronization.
- Delivered secure, BDEW/GDPR-compliant integration (AS2/OFTP2, RFC/IDoc, REST APIs, OAuth 2.0, Azure AD, AWS S3) achieving >99.5% uptime, <0.1% migration discrepancy, and RTO <4 hours.
- Applied BPMN to model and optimize the market communication processes.
Technologies: SAP IS-U, NScale, Salesforce Marketing Cloud, EDIFACT, OAuth 2.0, Azure AD, AWS S3, BPMN, Jira, Confluence, Draw.io
Eli R.
Last position:
Technical co-founder at AskTheLaws
- Create an AI legal assistant with modern ML capabilities.
- Implement RAG architecture, with data pipelines for legal data search.
- Use AWS Bedrock for LLM and embedding models and LangChain/LangGraph
- Python with FastApi for backend and React for frontend
Hardeep B.
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.
Clarissa H.
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.
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
Daniel C.
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Christof N.
Last position:
Senior Developer at Otto GmbH
- Further development of personalized advertising spaces on the Otto web shop
- Full-stack development in a Kanban-driven team of about 15 people
- Technologies: Microservices, Kotlin, Spring, Spring Boot, Gradle, MongoDB, HTML, JS, Node, SCSS, AWS
- Development process: Kanban; continuous integration with AWS CodePipeline and GitHub Actions
Discover over 15,000 top freelancers
Statistics of experts using Amazon Kinesis
Aggregated from the professional profiles of matched freelancers.
Experience
18 years (Germany: 17 years)
Position duration
3.3 years (Germany: 2.3 years)
Positions per freelancer
13 (Germany: 11)
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Telecommunication, Aerospace and Defense
Certification focus areas
Information Technology, Quality Assurance, Product Development
Bachelor's degree or higher
100% (Germany: 93%)
Master's degree or higher
86% (Germany: 57%)
Doctorate
14% (Germany: 18%)
Certifications per freelancer
4 (Germany: 5)
Most common languages
English, German, Spanish
Speak two or more languages
86% (Germany: 97%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Munich using Amazon Kinesis
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Amazon Kinesis 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%)
- Telecommunication (57%)
- Aerospace and Defense (43%)
- Automotive (43%)
- Education (43%)
- Banking and Finance (43%)
- Transportation (43%)
- Manufacturing (43%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Real-time foundation
Amazon Kinesis is a managed AWS service for collecting, processing and analyzing streaming data as it arrives. Companies use it for application events, clickstreams, operational telemetry, financial signals and connected-device data. Its core services include Kinesis Data Streams, Data Firehose and Managed Service for Apache Flink.
Core services
Kinesis Data Streams gives applications controlled access to continuously produced records. Data Firehose delivers streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon OpenSearch Service and third-party tools with limited infrastructure management. Managed Service for Apache Flink supports stateful stream processing with Java, Scala or Python.
Typical deliveries
- Design shards, partition keys, retention and consumer strategies for Kinesis Data Streams
- Build ingestion pipelines with producers, enhanced fan-out and checkpointing
- Configure Firehose transformations, buffering, compression and delivery destinations
- Create Flink jobs for enrichment, aggregation, filtering and windowed analysis
- Monitor throughput, latency, failures and operational cost across AWS accounts
Connected AWS skills
Strong Amazon Kinesis professionals usually work across the surrounding AWS data ecosystem. Their toolkit may include AWS Lambda, Amazon EventBridge, Amazon MSK, Amazon Glue, Amazon EMR, Amazon CloudWatch, AWS Identity and Access Management, Amazon S3 and infrastructure as code with Terraform or AWS CloudFormation. They also understand schemas, serialization formats such as JSON and Avro, and secure networking through Amazon VPC.
When specialists help
Companies bring in freelance expertise when batch pipelines cannot meet freshness requirements, when an existing stream suffers from hot shards or consumer lag, or when a proof of concept must become a resilient production service. A specialist can assess partition design, replay behavior, back-pressure, failure recovery, observability and data quality. In Munich, collaboration may combine remote delivery with on-site workshops and clear English or German communication.
Signs of quality
- Explains delivery semantics, ordering limits and duplicate-record handling clearly
- Designs for scaling, replay, throttling and regional resilience rather than only happy paths
- Tests producers and consumers under realistic load and failure conditions
- Uses least-privilege access, encryption and meaningful CloudWatch alarms
- Documents ownership, runbooks, schemas and handover decisions
The strongest professionals connect stream-processing choices to business needs. They distinguish when Kinesis is a fit from cases better served by Amazon MSK, Amazon SQS or a batch-oriented data platform. They leave behind measurable operational controls, understandable code and a pipeline the internal team can maintain.
Frequently asked questions
Need clarity? These are the questions we hear most often about Amazon Kinesis.
Amazon Kinesis is used to ingest and process data continuously instead of waiting for scheduled batches. Common applications include clickstream analysis, application monitoring, fraud signals, IoT telemetry, log processing and near-real-time dashboards.
Kinesis Data Streams is a managed AWS-native streaming service with shard-based capacity and integrated AWS security and monitoring. Amazon MSK provides managed Apache Kafka, which can be a better fit when a team needs Kafka APIs, Kafka ecosystem compatibility or existing Kafka operating practices.
A strong Amazon Kinesis specialist should understand AWS Lambda, Amazon S3, Amazon Glue, Amazon Redshift, Amazon OpenSearch Service and CloudWatch. Experience with Apache Flink, Terraform, IAM, VPC networking, schema management and observability is also valuable.
The right level depends on the system’s traffic patterns, compliance needs and failure tolerance. A simple Firehose delivery may need focused AWS data-pipeline expertise, while custom consumers, Flink processing, replay requirements and multi-account operations call for a specialist who has handled production streaming systems.
Amazon Kinesis is well suited to remote collaboration because its architecture, infrastructure and monitoring can be reviewed in shared AWS environments. Teams in Munich should agree early on workshop schedules, documentation standards and whether English, German or both are needed for technical and stakeholder communication.
Ask the specialist to explain partition-key choices, ordering guarantees, duplicate handling, consumer lag and recovery from downstream failures. Review an architecture diagram, test plan, IAM model and monitoring approach rather than judging the solution only by whether records arrive in a demonstration.
Amazon Kinesis may be unsuitable when the workload is small, strictly batch-oriented or already depends heavily on Kafka-specific clients and tooling. It can also be the wrong fit if the team cannot operate stream consumers, manage event schemas or define clear retention and replay requirements.
A freelance Kinesis professional can deliver an ingestion architecture, producer and consumer services, Firehose configurations, Flink jobs, Terraform or CloudFormation resources, dashboards, alerts, load tests and operational runbooks. They should also document partition strategy, data contracts, security decisions and handover steps.
The average hourly rate of freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects is 105 €, which corresponds to a daily rate of about 839 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects, 100% hold at least a Bachelor's degree, 86% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 3.3 years.
The most common languages among freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects are English (100%), German (86%), and Spanish (29%).
The most common industries among freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects are Information Technology (100%), Telecommunication (57%), and Aerospace and Defense (43%).
The most common business areas among freelancers in Munich, Germany who have used Amazon Kinesis in their recent projects are Information Technology (100%), Product Development (86%), and Project Management (71%).
Main locations of FRATCH Experts, who have recently used Amazon Kinesis
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 
Berlin Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
