
Amazon DynamoDB Experts in Hamburg
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Meet FRATCH Experts in Hamburg, who have recently used Amazon DynamoDB
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.
Mirco S.
Last position:
Co-Founder, CTO & Managing Director at Sourcera.ai (Venture Build)
Full overall responsibility: product, technology, compliance and go-to-market
- Delivered an enterprise MVP in 54 days, exceeding scope and schedule.
- Won a 250k € ARR anchor customer and built a sustainable enterprise sales pipeline in the first quarter.
- Paid PoCs with Zalando (35k €) and tesa (26k €), validating product-market fit with Tier-1 enterprise customers.
- Initiated ISO-27001 and TISAX certification processes. Left when the venture entered its next organizational phase.
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.
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
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.
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 DynamoDB
Aggregated from the professional profiles of matched freelancers.
Experience
22 years (Germany: 17 years)

Position duration
2.5 years (Germany: 2.3 years)

Positions per freelancer
19 (Germany: 11)

Top business areas
Information Technology, Product Development, Business Intelligence

Top industries
Information Technology, Transportation, Media and Entertainment

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
50% (Germany: 92%)
Master's degree or higher
25% (Germany: 54%)

Certifications per freelancer
1 (Germany: 2)

Most common languages
German, English, Dutch

Speak two or more languages
100%
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 Hamburg 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 Hamburg using Amazon DynamoDB
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 DynamoDB 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 (71%)
- Media and Entertainment (71%)
- Retail (71%)
- Banking and Finance (57%)
- Manufacturing (57%)
- Automotive (29%)
- Energy (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
DynamoDB in practice
Amazon DynamoDB is a fully managed NoSQL database for applications that need predictable performance, high availability, and flexible document or key-value data. It supports tables, primary keys, secondary indexes, streams, transactions, and fine-grained access through AWS Identity and Access Management. Teams use it for web and mobile backends, event-driven services, session data, catalogs, and high-traffic APIs.
Data modeling
Strong specialists start with access patterns rather than forcing relational habits into DynamoDB. They choose partition and sort keys, shape single-table or focused-table designs, and plan indexes, item collections, and data duplication deliberately. They also account for item size, consistency choices, conditional writes, transactions, and capacity behavior before implementation.
AWS ecosystem
DynamoDB work often sits inside a broader AWS architecture. Relevant tools and integrations include:
- AWS Lambda, API Gateway, and Amazon EventBridge for serverless workflows
- DynamoDB Streams with Lambda for change processing and projections
- Amazon Cognito, IAM, and AWS Key Management Service for access and encryption
- CloudFormation, AWS CDK, Terraform, and CI/CD pipelines for repeatable delivery
Typical deliverables
Companies bring in freelance expertise when a new service needs a durable data layer, an existing table suffers from inefficient access patterns, or a migration from a relational database requires careful redesign. Typical deliverables include data models, infrastructure definitions, application integrations, migration plans, monitoring dashboards, load tests, and operational runbooks. In Hamburg, remote collaboration may suit distributed teams, while on-site workshops can help align product, data, and infrastructure specialists.
Operational quality
Reliable DynamoDB systems depend on more than creating tables. Professionals evaluate throttling risks, hot partitions, retry behavior, pagination, backup and restore, point-in-time recovery, global tables, and disaster planning. They use CloudWatch metrics and structured logs to investigate latency, consumed capacity, failed requests, and stream processing without exposing sensitive data.
Choosing expertise
Look for specialists who can explain why a key design fits real access patterns and where its trade-offs appear. Practical evidence includes production migrations, serverless integrations, automated infrastructure, tested recovery procedures, and clear documentation. For Hamburg teams, confirm whether the professional can work in the required language and coordinate effectively across remote or on-site sessions.
Frequently asked questions
Curious about Amazon DynamoDB? Here are the answers that come up again and again.
Amazon DynamoDB is used for managed key-value and document storage in applications that require low-latency access and elastic scaling. Common examples include serverless APIs, user sessions, product catalogs, IoT data, event processing, and high-traffic digital services.
DynamoDB is built around known access patterns, partition keys, and denormalized data rather than joins and flexible ad hoc queries. A relational database may be a better fit for complex relationships, reporting, or workloads that depend heavily on multi-table queries.
Amazon DynamoDB is often attractive when a team wants a fully managed AWS-native service with integrated security, monitoring, backups, and serverless connectivity. MongoDB can offer a broader document-query experience, while Cassandra may suit teams that need a more portable distributed database approach.
DynamoDB work benefits from knowledge of AWS Lambda, API Gateway, IAM, CloudWatch, EventBridge, and infrastructure as code. Experience with application languages, event-driven design, data migration, testing, and operational security is also valuable.
Amazon DynamoDB projects need enough practical experience to model real access patterns and anticipate operational risks. A straightforward table integration may need focused support, while migrations, global deployments, or complex event flows call for a specialist who has handled comparable production systems.
DynamoDB work is well suited to remote collaboration because modeling, infrastructure, code reviews, and monitoring can be handled through shared tools. Hamburg teams should define workshop needs, working hours, documentation standards, and German or English language expectations before the engagement starts.
Amazon DynamoDB quality is visible in the reasoning behind the data model, not just in a working table. Ask for a clear explanation of keys, indexes, consistency, retry handling, capacity risks, recovery, security, and how the design will be tested under realistic access patterns.
DynamoDB specialists should clarify expected access patterns, traffic behavior, consistency needs, retention, compliance constraints, recovery objectives, and surrounding AWS services. They should also confirm ownership of infrastructure, observability, migration testing, documentation, and ongoing operational support.
The average hourly rate of freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects is 98 €, which corresponds to a daily rate of about 787 € based on an 8-hour working day.
Of the freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects, 50% hold at least a Bachelor's degree and 25% hold at least a Master's degree.
On average, freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects are German (100%), English (100%), and Dutch (14%).
The most common industries among freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects are Information Technology (100%), Transportation (71%), and Media and Entertainment (71%).
The most common business areas among freelancers in Hamburg, Germany who have used Amazon DynamoDB in their recent projects are Information Technology (100%), Product Development (100%), and Business Intelligence (71%).
Main locations of FRATCH Experts, who have recently used Amazon DynamoDB
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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