Amazon Kinesis Experts in Berlin
in minutes with vetted freelancers and the power of AIHire experts who design streaming pipelines, tune Kinesis Data Streams and Firehose, and build real-time event workflows for analytics and operational monitoring. Fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Amazon Kinesis
Alexander Zhirov
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 Kannan
Last position:
Freelance Software Engineer at Zalando SE
- Support Authorization as a Service initiative for enterprise-scale authorization platform
- Incorporate comprehensive observability solutions into authorization infrastructure
- Provision and manage AWS infrastructure for authorization services
- Mentor development team on AWS and Kubernetes best practices
- Tech Stack: Java/Kotlin, Golang, Python, OPA, Spring Boot, AWS, Kubernetes, Terraform, ELK Stack, Prometheus, Grafana
Jan Krol
Last position:
Data Expert at Manufacturing
Meisam Ghafarlangroudi
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 Mohamed
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 Richter
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Ilya Isakov
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 Petersen
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: 2.4 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Retail, Automotive
Bachelor's degree or higher
86% (Germany: 92%)
Master's degree or higher
29% (Germany: 54%)
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 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Berlin 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 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Streaming basics
Amazon Kinesis is used to move and process data as it happens. Companies use it for clickstream tracking, application events, log ingestion, IoT feeds, and alerting. It fits systems that need low-latency data flow instead of batch transfers.
Core services
- Kinesis Data Streams for custom streaming applications
- Kinesis Data Firehose for delivery into storage and analytics tools
- Kinesis Data Analytics for SQL-based stream processing
- Integration with Lambda, S3, Redshift, and OpenSearch
When experts help
Teams bring in freelancers when a stream starts lagging, delivery fails, or data needs a cleaner event model. They also help during migrations from older ingestion tools or when a product team in Berlin needs real-time features without slowing the release plan.
Skills that matter
Strong specialists know shard planning, throughput limits, ordering, retention, and replay behavior. They also understand IAM, monitoring, dead-letter patterns, and how to keep producers and consumers stable under load. Good work is practical, readable, and easy to operate.
Common delivery work
- Event-driven backend design
- Stream processing for dashboards and alerts
- Log and telemetry pipelines
- Delivery to data lakes and warehouses
What sets them apart
A good Amazon Kinesis expert does more than connect services. They design for backpressure, scaling, recovery, and clear ownership of each stream. In Berlin, that often means working smoothly with product, platform, and data teams across English and German setups.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Amazon Kinesis.
Amazon Kinesis is used to handle data that arrives continuously, such as app events, logs, tracking data, and device signals. Companies use it when they need fast processing, reliable delivery, or downstream analytics without waiting for batch jobs.
Amazon Kinesis is a managed AWS service, so teams often choose it when they want less infrastructure work and tighter AWS integration. Kafka can offer more control and portability, but it usually asks for more operational ownership. The better choice depends on whether the priority is managed simplicity or platform flexibility.
A strong Kinesis specialist usually knows Lambda, IAM, S3, CloudWatch, and one or more analytics targets such as Redshift or OpenSearch. They should also be comfortable with event modeling, retry handling, and monitoring stream health. Those skills matter because Kinesis is rarely used on its own.
Amazon Kinesis expertise matters when a team is building real-time dashboards, log pipelines, alerting flows, or event-driven services. It also helps when a stream is already running but performance, cost, or delivery reliability needs improvement. Simple one-off ingestion jobs usually need less specialist input.
Yes, Amazon Kinesis work is often well suited to mixed remote teams. The technical tasks can be handled remotely, while workshops on data ownership, incident handling, and security may benefit from a few on-site sessions in Berlin. Clear access and documentation matter more than location.
Look for real delivery work with Kinesis Data Streams, Firehose, and monitoring, not just service familiarity. Ask how they would size shards, handle retries, and keep consumers stable during load spikes. Good specialists can explain trade-offs clearly and show how they debug production issues.
No, Amazon Kinesis is also used for operational alerts, log routing, near-real-time enrichment, and feeding storage layers for later analysis. Some teams use it mainly as a transport layer, while others build processing logic on top. The right design depends on latency and reliability needs.
Useful adjacent experience includes event-driven architecture, data modeling, observability, and AWS security. A freelancer who understands producers, consumers, schema changes, and failure recovery will usually deliver better results. That background helps when the stream is part of a larger platform.
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 746 € 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.
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!

Munich