Amazon Kinesis Experts in Berlin
, matched in minutes from over 15,000 CVs with the power of AIHire experts who design streaming architectures, connect Kinesis Data Streams with AWS analytics services, and deliver real-time dashboards or event-driven applications. FRATCH matches you quickly with precise, vetted and available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Amazon Kinesis
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Santhosh K.
Last position:
Freelance Software Engineer at Zalando SE
- Drive migration of enterprise authorization platform from Styra DAS to open-source OPA via Skipper (Zalando's Golang-based ingress proxy) integration
- Optimise k8s resources and integrate native Prometheus metrics with OPA
- Migrate from internal monitoring solution to Prometheus CRs + Dash0
Tech Stack: Java/Kotlin, Golang, Python, Spring Boot, AWS, Kubernetes, Docker, OpenTofu, Prometheus, Grafana
Jan K.
Last position:
Data Expert at Manufacturing
Meisam G.
Last position:
Senior AI Engineer / Data Scientist at Geeks Ltd (WordUp)
Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.
- Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
- Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
- Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
- Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
- Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.
Khaled M.
Last position:
Senior/Staff Backend Engineer at Heycar (Mobility Trader GmbH)
- Heycar is a leading automotive platform redefining the used car market through intelligent data pipelines, multi-tenant services, and dealer-focused tooling. I led initiatives across backend architecture, data ingestion, and identity management to enhance scalability, reliability, and developer productivity.
- Ingestion Platform: Designed a unified ingestion platform with YAML-based configuration, enabling new dealer data pipelines to be onboarded without code changes, cutting setup time from ~2 months to 2-3 days and improving scalability by 40%.
- Keycloak Leadership: Acted as the company's Keycloak expert, scaling it for multi-tenant identity management and extending functionality with custom plugins and delegated admin APIs.
- Back-Office Tooling: Developed a back-office application integrated with Salesforce, enabling dealers to manage inventory, convert leads, and handle support requests in real time.
- Multi-Tenant Migration: Collaborated across backend teams to migrate Heycar's core services into a unified multi-tenant cluster, ensuring high availability.
- Frontend CI Optimization: Optimized monorepo delivery by implementing CircleCI dynamic config with NX, deploying only affected UI projects and drastically cutting build times.
- Observability & Mentorship: Enhanced monitoring and release reliability while mentoring backend engineers and improving code review standards.
Christian R.
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Ilya I.
Last position:
Data/Platform/Software Engineer/SRE at IT Consulting
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
Henning P.
Last position:
Backend Systems Development at Deutsche Bank/DWS/Morgenfund
- Developed backend systems for the DWS Investment App, a white-label investment solution (robo-advisor), and an investment solution for institutional clients.
- Java 8-17, Kotlin, Spring Boot, Spring MVC, OpenAPI 3.0, JPA, JDBI, Oracle, Hazelcast, JXLS, Apache POI, Apache PDFBox, Apache Kafka & Avro, Active MQ, Elasticsearch, React Native, Spock Test, IntelliJ IDEA, Kubernetes, Helm, Microservices/Netflix-Stack, TeamCity, Splunk.
- Kanban team, continuous integration.
- Migrated existing applications from Deutsche Bank's private cloud environment to Azure as part of a carve-out.
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
2.8 years (Germany: 2.3 years)
Positions per freelancer
9 (Germany: 11)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Retail, Automotive
Bachelor's degree or higher
86% (Germany: 93%)
Master's degree or higher
29% (Germany: 57%)
Certifications per freelancer
1 (Germany: 5)
Most common languages
German, English, Arabic
Speak two or more languages
100% (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 Berlin 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 Berlin 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 (88%)
- Retail (50%)
- Automotive (38%)
- Banking and Finance (38%)
- Professional Services (38%)
- Telecommunication (38%)
- Transportation (25%)
- Media and Entertainment (25%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Real-time streaming
Amazon Kinesis is a managed AWS service family for collecting, processing and analyzing streaming data as it arrives. Companies use Kinesis Data Streams for custom consumers, Kinesis Data Firehose for delivery into storage and analytics systems, and Kinesis Data Analytics for near-real-time processing. It supports data from applications, devices, clickstreams, logs and operational systems.
Core services
The right design depends on how data should be ingested, transformed, stored and consumed.
- Kinesis Data Streams captures ordered records across scalable shards and consumer applications.
- Kinesis Data Firehose delivers streams to destinations such as Amazon S3, Redshift, OpenSearch Service and third-party tools.
- Kinesis Data Analytics processes streaming data with SQL or Apache Flink applications.
- Amazon CloudWatch, AWS Lambda and AWS Glue support monitoring, transformation and operational workflows.
Common applications
Kinesis specialists deliver streaming systems for use cases where delayed data would limit decisions or user experience.
- Build event pipelines for clickstream, application and IoT data.
- Create fraud detection, alerting and operational monitoring flows.
- Feed real-time dashboards, data lakes and analytics warehouses.
- Connect microservices through durable, observable event streams.
- Migrate batch-oriented workloads toward continuous processing.
Skills around Kinesis
Strong professionals combine Kinesis with AWS identity, networking and storage services. They work with IAM, VPC, S3, Lambda, DynamoDB, Redshift, OpenSearch Service and CloudWatch, while understanding partition keys, retention, throughput and consumer behavior. Apache Flink, SQL, Python, Java and infrastructure as code are valuable when stream processing becomes complex.
When to hire specialists
Companies bring in freelance Amazon Kinesis expertise when an existing pipeline loses records, falls behind, costs too much or becomes difficult to operate. Specialists can assess ingestion patterns, choose between Streams and Firehose, define recovery behavior, tune partitioning and establish useful alerts. In Berlin, they may work remotely or join local product, data and cloud teams for workshops and delivery.
Quality signals
A capable professional explains the trade-offs between latency, durability, ordering, replay and operational effort before proposing an architecture. They document event schemas, failure handling, permissions and deployment steps, then validate the design with realistic load and recovery tests. Look for experience connecting Kinesis to the systems your company already runs, clear observability practices and communication suited to both technical and business stakeholders.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Amazon Kinesis.
Amazon Kinesis is used to ingest, process and deliver data that arrives continuously. Typical workloads include application telemetry, clickstream analysis, IoT events, fraud signals, live dashboards and event-driven workflows.
Amazon Kinesis is designed for managed streaming with ordered records, replayable retention and AWS-native consumers. Amazon MSK suits teams that need Apache Kafka compatibility and deeper cluster control, while Amazon SQS is primarily a message queue for decoupling workloads rather than a high-volume event stream.
A strong Amazon Kinesis specialist usually understands IAM, Lambda, S3, Redshift, OpenSearch Service, CloudWatch and VPC networking. Apache Flink, SQL, Java or Python can also matter when the project requires stateful transformations or complex stream processing.
The required experience depends on the data volume, delivery guarantees, integrations and operational risk. A small ingestion flow may need focused AWS streaming knowledge, while a critical platform benefits from someone who has designed partitioning, replay, failure recovery, observability and infrastructure automation.
Amazon Kinesis is well suited to remote collaboration because its architecture, infrastructure and monitoring can be reviewed in shared AWS environments. Teams in Berlin should agree on documentation, incident communication and working language early, especially when specialists collaborate across locations.
Kinesis Data Streams fits applications that need custom consumers, controlled processing, replay and fine-grained handling of records. Firehose is more convenient when the main requirement is managed delivery into supported destinations with limited stream-processing logic.
Ask a candidate to explain partition-key choices, shard or capacity planning, duplicate handling, ordering limits and recovery procedures. A strong Amazon Kinesis professional also shows how they monitor lag, errors and delivery outcomes, and can describe a design in terms of measurable reliability goals.
Amazon Kinesis work often involves more than configuring a stream: professionals may define event schemas, secure IAM policies, connect consumers, automate deployments and support production incidents. Familiarity with AWS cost controls, CloudFormation or Terraform and downstream analytics systems makes it easier to deliver a complete solution.
The average hourly rate of freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects is 93 €, which corresponds to a daily rate of about 745 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects, 86% hold at least a Bachelor's degree and 29% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects are German (100%), English (100%), and Arabic (13%).
The most common industries among freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects are Information Technology (88%), Retail (50%), and Automotive (38%).
The most common business areas among freelancers in Berlin, Germany who have used Amazon Kinesis in their recent projects are Information Technology (100%), Product Development (75%), and Business Intelligence (63%).
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 
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