AWS Lambda Experts in Frankfurt
, matched fast from over 15,000 CVs with the power of AIHire experts who design event-driven services, optimize serverless costs, and connect AWS Lambda with API Gateway, SQS, DynamoDB, and CloudWatch. FRATCH matches you precisely with vetted, available freelancers for remote or on-site work in Frankfurt.
Meet FRATCH Experts in Frankfurt, who have recently used AWS Lambda
Patrick L.
Last position:
Senior GenAI Fullstack Developer at SBH (Schulbau Hamburg)
Remote freelance role focused on Agentic AI strategy, secure application patterns, and reusable agentic workflows for a government agency.
- Development and implementation of an open-source Agentic AI strategy for a government agency, with a focus on GDPR, security, and self-hosted solutions
- Development of reusable agentic workflows and business applications that enable non-technical employees to solve business problems independently
- Implementation of nine business applications with Single Sign-On (SSO) and Azure PostgreSQL integration on Hetzner Linux servers
Techstack: Python, Streamlit, Anthropic SDK (Claude), Azure, Linux, PostgreSQL, MS SQL, Angular
Michael H.
Last position:
Frontend Developer at RTL Tech
- Development and optimization of the RTL+ frontend application for SmartTV and set-top box platforms with React and Next.js.
- Key role in the technical coordination of developers within the team and in coordinating implementation.
- Central interface to adjacent teams to simplify development processes and improve cross-team alignment.
- Improved frontend performance, stability, and rendering behavior on low-powered devices in a restricted runtime environment.
- Implemented a frontend testing strategy with Jest, React Testing Library, and Playwright.
- Implemented accessibility improvements according to WCAG 2.2 and WAI-ARIA.
- Integrated Didomi Consent Management as a contribution to increasing ad monetization on streaming platforms.
- Used AI-supported engineering workflows with Cursor for structured implementation, refactoring, and faster problem solving.
Technologies used: React, Next.js, TypeScript, JavaScript, GraphQL, Apollo Gateway, Zustand, Tailwind CSS, Styled Components, React Testing Library, Playwright, Jest, HTML5, CSS3, AWS Lambda, EC2, CloudFront, S3, GitLab CI/CD, NX, Cursor
Helge B.
Last position:
Solution Architect at Deutsche Bahn
- Responsible for the end-to-end application and integration architecture for the S-Bahn Hamburg maintenance digitalisation program. A highlight is the introduction of robots and permanently installed camera gates to automate vehicle inspections, allowing AI image algorithms to assess the condition of trains during operation.
- Deutsche Bahn has one of the largest SAP PM implementations in the world, which is a central component of this digitalisation.
Jan M.
Last position:
Founder, Senior Solution Architect, Team Lead, Senior DevOps Engineer at CreArt IT GmbH
- Hands-on solution architect
- Digital product development - SaaS
- Strategic consulting on software architecture, cloud migration, and DevOps processes
- Coaching SE developers and IT architects
Ulm P.
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Ashkan Z.
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Anton R.
Last position:
AI-Engineer at Publicly traded company, industrial safety technology
- Designed and implemented the agent-based AI architecture for a company-wide platform to securely deploy LLM-based agents
- Designed and implemented end-to-end RAG pipelines from multiple sources: document preprocessing, chunking strategies for different document types, embeddings, retrieval with re-ranking, and robust prompt orchestration
- Developed a modular context engineering framework with skill architecture, context isolation, and dynamic resource management; human-in-the-loop control for enterprise tool integrations
- Built the CI/CD pipeline, testing strategy, tracing on the software side as well as automated LLM and agent evaluations, red team testing and tracing, and handed over to a reproducible production environment (ISO27001 and SOC2 compliant)
Kevin M.
Last position:
Backend & Infrastructure Engineer at Mileo Systems GmbH
- Engineered production-ready Azure environments using Terraform, ensuring consistent infrastructure parity across VNets and Resource Groups
- Implemented Microsoft Fabric tenant and workspace architecture for multi-stage Medallion data processing pipelines
- Designed secure data pathways using Managed Private Endpoints for isolated Azure Storage access
- Managed Service Principals and authentication tokens for secure REST API integrations
Tan P.
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Roman K.
Last position:
Senior Data Engineer / Cloud Architect at DB Systel
- Development of a central billing app for cloud costs at DB
- AWS
- Python
- AWS CDK
- RDS
- Spark (PySpark)
- Glue
- Lambda
- CI/CD (GitLab)
- React/Typescript
- data optimization
- Scrum
Ritika S.
Last position:
AWmOpsRtKekEX(CPEliRenIEtN: CInEfoSrs.yDs,aHtaitAarcchhiiEtencetr(gAyW) S)
Global marketing analytics for Hitachi Energy as part of a global data modernization initiative aiming to enhance data retention, historical data availability and provide Eloqua's 2-year retention for remote interaction reporting and analytics.
Analyzed Eloqua's default retention policy and identified risk of data loss for records older than two years.
Designed and implemented historical data preservation strategy by creating transformed tables in the target data platform to archive older data while ensuring data quality dashboards.
Collaborated with the Power BI team to re-point dashboards from raw Eloqua imports to the newly created archival layer.
Leveraged Jira to track and manage data engineering tasks, bugs, and feature requests across Agile sprints; coordinated backlog prioritization and task assignment to align data pipeline development with business needs.
Power BI dashboard optimization:
Worked closely with business stakeholders to assess and understand reporting needs for reverse customer data.
Designed and implemented incremental refresh in Power BI to ensure daily updates without full data reloads.
Collaborated with Azure data engineers to optimize data processing and publication pipelines.
Stakeholder communication & data modeling:
Acted as liaison between Group Data Office and Technology Office to align data modelling standards.
Gathered requirements from data engineering team and participated in weekly status meetings to provide implementation updates and resolve blockers across teams in Germany, Poland, and India.
Documentation & quality assurance:
Prepared end-to-end technical design documentation, data flow diagrams, and Power BI audit guides for future reference.
Participated in UAT sessions with business users to validate data outputs and report accuracy.
Leonard H.
Last position:
Freelance Software Engineer & Cloud Architect at Leonard Hußke - IT Solutions
- Evaluation of potential providers (Snowflake vs Databricks) and design of the analytics data platform using Databricks
- Data storage and ingestion layer with Amazon S3
- Creation of ETL processes and data transformations with AWS Glue and Databricks Notebooks
- Orchestration with AWS Glue Workflow, Databricks Workflow and Databricks DLT
- Processing of unstructured data, including text, images and video
- Databricks workspace setup and administration
- Implementation of a medallion architecture to ensure data quality
- Evaluation of potential BI tools (Power BI, AWS Quicksight, Tableau)
- Establishment of MLOps using MLFlow
- Introduction of data governance and data lineage using Unity Catalog
Doğan Can U.
Last position:
E-Commerce Developer at The Quality Group
Backend development for shops related to the “ESN” and “More Nutrition” shops
Technologies included: PHP, Symfony 6, Bref, AWS (SQS, Lambda), Terraform, Akeneo API
Discover over 15,000 top freelancers
Statistics of experts using AWS Lambda
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 16 years)
Position duration
1.8 years (Germany: 2.1 years)
Positions per freelancer
14 (Germany: 11)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Government and Administration, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100% (Germany: 93%)
Master's degree or higher
45% (Germany: 60%)
Doctorate
9%
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 99%)
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 Frankfurt 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 Frankfurt using AWS Lambda
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.
AWS Lambda 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 (92%)
- Government and Administration (54%)
- Banking and Finance (46%)
- Healthcare (46%)
- Professional Services (46%)
- Education (38%)
- Insurance (38%)
- Transportation (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Serverless execution
AWS Lambda is a managed compute service that runs code in response to events without requiring teams to provision or maintain servers. Companies use it for APIs, data processing, scheduled automation, file handling, and event-driven workflows. Lambda functions scale with demand and charge based on execution, making architecture and observability important from the start.
Typical applications
Lambda supports workloads across web, data, and operations teams:
- Build backend endpoints with API Gateway and authorizers
- Process uploads from Amazon S3 and messages from SQS
- Transform streams, events, and files in near real time
- Run scheduled jobs with EventBridge
- Automate infrastructure and internal business workflows
AWS ecosystem
Strong specialists work across the AWS services around Lambda, including IAM, CloudWatch, X-Ray, DynamoDB, Step Functions, EventBridge, S3, and API Gateway. They select suitable runtimes, package dependencies, manage environment variables, and define infrastructure with AWS SAM, AWS CDK, Terraform, or CloudFormation. Familiarity with containers and CI/CD also helps when deployments become more complex.
When to bring in experts
Companies often need freelance expertise when a monolith is being decomposed, a serverless proof of concept must become production-ready, or event processing is unreliable. Specialists can improve cold-start behavior, concurrency controls, retries, permissions, deployment pipelines, and monitoring. In Frankfurt, they may support local teams on-site while coordinating with distributed product and security groups remotely.
Quality signals
A capable AWS Lambda professional explains trade-offs instead of treating serverless as a default answer. Look for experience with idempotency, timeouts, dead-letter handling, least-privilege IAM, structured logs, testing, and rollback strategies. Good deliverables include clear diagrams, repeatable infrastructure, useful alerts, documented runbooks, and predictable behavior under failure.
Collaboration and delivery
Lambda work often crosses application, data, security, and operations boundaries. Freelancers should communicate function contracts, event schemas, ownership, and operational limits clearly. English is common in international AWS teams, while German can support collaboration with Frankfurt-based stakeholders. A strong engagement ends with maintainable code, secure configuration, deployment documentation, and a practical handover.
Frequently asked questions
What clients ask us most about AWS Lambda — answered in short.
AWS Lambda runs small units of code in response to events, requests, schedules, or messages. Companies use it for serverless APIs, file and stream processing, workflow steps, automation, and integrations without managing application servers.
AWS Lambda removes server management and can scale execution automatically, which suits event-driven and variable workloads. Containers or virtual machines offer more control over runtime behavior, networking, process lifetime, and long-running services, so the right choice depends on operational and performance needs.
A strong AWS Lambda specialist usually understands IAM, API Gateway, S3, SQS, EventBridge, DynamoDB, CloudWatch, and Step Functions. Infrastructure as code, CI/CD, security, testing, and one or more supported programming languages are also valuable.
The required depth depends on the task. A simple function may need focused runtime and deployment knowledge, while a production migration calls for experience with event design, failure handling, observability, security, cost control, and integration across AWS services.
Yes. AWS Lambda work is usually well suited to remote collaboration because code, infrastructure, logs, and deployments are shared through cloud tools. On-site sessions in Frankfurt can still help with architecture workshops, stakeholder alignment, or regulated delivery processes.
Ask how the specialist handles retries, duplicate events, timeouts, permissions, dependency packaging, and observability. Review infrastructure definitions, tests, deployment workflows, dashboards, and documentation rather than judging only the function code.
AWS Lambda is designed for short-lived, event-triggered execution rather than persistent processes. Long-running workloads may fit container services, batch processing, or virtual machines better, while Lambda can still coordinate those systems through events and workflows.
Common risks include uncontrolled concurrency, inefficient dependencies, weak IAM policies, hidden retry behavior, poor tracing, and tightly coupled event schemas. Experienced AWS Lambda professionals make these limits visible and design for failure, replay, idempotency, and safe rollback.
The average hourly rate of freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects is 92 €, which corresponds to a daily rate of about 739 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects, 100% hold at least a Bachelor's degree, 45% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects are German (100%), English (100%), and French (15%).
The most common industries among freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects are Information Technology (92%), Government and Administration (54%), and Banking and Finance (46%).
The most common business areas among freelancers in Frankfurt, Germany who have used AWS Lambda in their recent projects are Information Technology (100%), Product Development (85%), and Business Intelligence (77%).
Main locations of FRATCH Experts, who have recently used AWS Lambda
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 
Stuttgart Request a free demo
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Philipp Thomaschewski
FRATCH CEO
