
AWS Lambda Expert
to ship scalable event-driven services with vetted professionals matched in minutesHire experts who design serverless APIs, build event-driven workflows with Amazon EventBridge and SQS, and connect Lambda functions to AWS data services. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts who have recently used AWS Lambda
Vasco F.
Last position:
Senior AI Engineer (Freelance) at RWE
Databricks Architecture & AI Data Products [Databricks Apps · Unity Catalog · Delta Lake · Lakebase · Asset Bundles · Azure DevOps · MCP]
- Designed a layered Databricks financial data architecture: Apps/FastAPI for serving, modular Python calculation engines, SQL/Delta for governed analytics, and Unity Catalog Volumes for versioned workbook outputs.
- Integrated Lakebase PostgreSQL operational data with SQL warehouse analytics, keeping transactional and analytical access separate through App service-principal identity, short-lived credentials and controlled, read-only data interfaces.
- Defined DEV/TST/PRD deployment architecture using Databricks Asset Bundles and automatic Azure DevOps CI/CD, with reusable environment configurations, OAuth M2M identities and automated application/resource lifecycle management.
- Designed access boundaries across Apps, SQL warehouses, Unity Catalog tables/functions/Volumes and secret scopes; separated deployment, application and SQL identities through declarative resource permissions and environment-specific authentication.
- Built serverless Spark pipelines for geospatial reference data and a traceable storage architecture combining immutable Volume artifacts, revision lineage and append-only Delta history with durable audit-event delivery.
- Connected AI Hub agents to governed Databricks financial workflows through typed REST/MCP interfaces; implemented CAPEX/OPEX, commercial, lease and IRR/NPV engines with scenario validation and workbook consistency checks.
Sergej G.
Last position:
IT Consultant and Software Developer at Görzen Consulting
- End-to-end ownership of client projects, from requirements to rollout
- CTO of Edumix, a platform for interactive learning content (not yet released)
- CTO of a B2B AR app with indoor navigation and a digital twin (Matterport)
- OnePortrait: migration from Node.js/Nuxt to React, Next.js and Go
- Interactive Three.js mosaic featuring thousands of images
- Daily use of AI tools and coding agents (agentic coding)
Technologies: React, Next.js, Go, Node.js, Unity (Editor Extensions, UaaL), Flutter, iOS, .NET MAUI, Supabase/PostgreSQL, Three.js
Projects: Edumix, AR Indoor Service App, OnePortrait
Caleb C.
Last position:
Senior Python Backend Engineer at Simon-Kucher
Transmission system operator – network provisioning platform (team lead)
- Designed the saga orchestrator in Python that provisions network fabrics with rollback.
- Split IP, identity, and resource allocation into bounded contexts with their own databases and typed clients.
- Implemented data access using DDD repositories and units of work, with no SQL in the domain code.
- Required integration tests using real PostgreSQL and RabbitMQ containers, and API fuzzing for every service.
- Introduced an agent workflow where a spec starts each change and a human approves every merge.
- Rolled out OpenTelemetry auto-instrumentation through GitOps across eighteen Kubernetes clusters.
- Led incident response for stuck provisioning and recorded every outage as a post-mortem.
Languages and software used: Python, FastAPI, Pydantic v2, SQLAlchemy async, PostgreSQL, RabbitMQ, Celery, pytest, testcontainers, schemathesis, Helm, Flux CD, GitLab CI, OpenTelemetry, pi coding agent.
Software product company – datacenter simulation SaaS (backend development)
- Built the asynchronous simulation pipeline as the second-largest contributor among more than twenty team members.
- Tagged every image by commit SHA and semver in the GitHub Actions deployment workflows.
- Diagnosed the RabbitMQ memory alarm that froze every simulation and fixed the limits in the Helm chart.
- Converted the test suite to function-style pytest, with coverage reported in every pipeline.
Languages and software used: Python, FastAPI, SQLAlchemy, Alembic, Celery, RabbitMQ, Redis, PostgreSQL, S3, EKS, Helm, Keycloak, GitHub Actions, pytest, mypy, ruff, SonarQube.
Internal AI platform – model serving and telemetry
- Built the FastAPI service that deploys open-weight models on GPU tiers as OpenAI-compatible endpoints.
- Upgraded production EKS by two Kubernetes minor versions and fixed zone-bound storage faults.
- Traced every model call, including its token count, cost, and latency, through the OpenTelemetry operator.
Languages and software used: Python, FastAPI, vLLM, LangGraph, pydantic-ai, OpenAI and Anthropic APIs, EKS, Helm, Flux CD, Terraform, GitLab CI, OpenTelemetry, Grafana.
Mansharan K.
Last position:
MS Fabric | Power BI Consultant at Gropyus Technologies GmbH
- Architected an enterprise Fabric-based data-product governance framework, authoring data contracts and schema-validation KPIs to enforce completeness, freshness and SLA standards across reporting data products.
- Operationalized pipeline observability by integrating Dagster orchestration data into automated data-health reporting, proactively validating data integrity and pipeline reliability before production reporting layers refresh.
- Established BI-as-Code and end-to-end governance through Git-based version control, CI/CD and Alpha→GA release management, strengthening lineage, schema-drift detection and production change traceability.
Luigi C.
Last position:
Senior Full Stack Developer at Almuc Advertising GmbH
- Applied modern JavaScript features, including ES6+ syntax, destructuring, modules, array methods, and asynchronous programming, to develop efficient and readable frontend code.
- Implemented frontend integration patterns for PHP and Laravel backend services, connecting React interfaces to REST APIs and handling structured JSON data.
- Developed interactive, functional component-based frontend applications using React Hooks, JavaScript, and TypeScript, alongside backend applications and RESTful APIs using Python, Django, Flask, and FastAPI, focusing on reusable components, modular architecture, maintainability, and efficient data processing.
- Maintained a dynamic portfolio platform using PHP, Laravel, Livewire, and MySQL, implementing end-to-end functionality across frontend interfaces, backend services, and database operations.
- Validated server-side request handling, routing, middleware, and form validation using Laravel features to support reliable application workflows and consistent data processing.
- Designed and managed relational database structures using MySQL and Laravel Eloquent ORM, implementing data models, relationships, database migrations, and efficient queries for content management.
- AI-powered applications integrating Large Language Models (LLMs) through external APIs and locally hosted models, exploring practical use cases for conversational AI, intelligent automation, and AI-assisted workflows.
- Built local AI applications and developer tools for running, configuring, and interacting with locally hosted language models, gaining experience with local inference, model integration, and privacy-conscious AI workflows.
- Explored Retrieval-Augmented Generation (RAG) approaches to combine language models with external knowledge sources, enabling context-aware responses based on relevant application data and retrieved information.
- Integrated AI services with backend APIs and application components, developing reusable modules for model communication, response processing, error handling, and data exchange.
Deniel H.
Last position:
Shareholder & Senior Engineer, Product and Go-to-Market at Continua Systems GmbH
Consulting and software for intralogistics automation (AGV/FTS) · Product lines AGVHub (independent AGV project consulting, layout editor) and OneBob (all-in-one business software for small teams)
- Designed and planned the implementation of a supervisory control system for a bakery production line (engineering customer, kick-off workshop 08/2025): three development stages, eight acceptance-ready milestones, batch traceability, AGV integration with RFID, Vue frontend.
- Discovery and requirements discussions with plant logistics and IT teams at industrial customers (life science, aviation, steel, engineering): translated supervisory control, ERP interface, and VDA 5050 requirements into architecture and requirements specification structures.
- Go-to-market automation and analytics: Bing and Meta campaigns, LLM-supported LinkedIn content pipeline, performance dashboards for partners and sales.
- Expert posts on LinkedIn about robotics and intralogistics: around 170,000 impressions across 41 posts (03 to 08/2026).
Nab R.
Last position:
Freelance Senior IT Consultant at FourEnergy GmbH
Semir A.
Last position:
Engineering Manager at Grafana Labs
- I lead a team of 10 engineers across EMEA split into 2 squads (ingest and query), focused on developing the next generation of logging systems.
- Leading the Loki team in Europe, overseeing the logging solutions at Grafana. I manage a diverse team of engineers, ranging from mid-level to principal, ensuring we deliver top-tier results.
- One of our key achievements has been the successful development and launch of ExploreLogs and AdaptiveLogs.
Simon K.
Last position:
Fullstack Developer at RTL Technology GmbH
- Development of a browser-based video logger for the automated enrichment of metadata to optimize video search and categorization in the company’s editorial tool. The platform enables editors to efficiently analyze video content and add additional information.
- AI-supported scene recognition for the automatic generation of video shots and time markers
- Automatic transcription and speech analysis for extracting relevant content
- Enhanced metadata management to improve search and archiving functions
- Event-driven architecture in the frontend (Angular, TypeScript)
- Backend integration (.NET) with video streaming and data processing
Patrick D.
Last position:
Fullstack Developer
- SPA for automated communication of medical findings with role-based access (Sanctum)
- Server-side LLM integration (OpenRouter) with structured processing
- Automated sending via SMS/voice call (Twilio, ElevenLabs) with queue + status retry
- Full test coverage with 80+ documented test cases
Technologies: PHP, Laravel, LLM API (OpenRouter), Twilio, ElevenLabs, Laravel Sanctum, PHPUnit, Playwright, Docker, REST
Ahmed M.
Last position:
Senior Full-Stack Engineer at NEW NETZ
- Built more than 15 frontend applications and more than 10 backend services across internal tools, back-office workflows, and external portals for installers and end customers
- Automate build and release workflows with TypeScript and Azure DevOps
- Mentor junior engineers through code reviews and technical guidance
- Integrate AI-assisted and agentic development practices into engineering workflows
- Coordinate user experience decisions with UX designers
Tech Stack: Claude Code, Codex, AWS (S3, Lambda, AppSync, Resolver), Next.js App Router, ReactJS, NuxtJS, Vue.js, Storybook, JavaScript, TypeScript, GraphQL, Azure DevOps
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
Aweem A.
Last position:
Senior Java Developer at Folio3
- Architected, developed, and maintained scalable backend services using modern Java (17/21), Kotlin, and Spring Boot for high-traffic, performance-critical platforms.
- Served as a technical leader for complex initiatives, taking features from inception through deployment, and implementing runtime validation layers using advanced LLM APIs with secure guardrails.
- Optimized PostgreSQL schemas and query efficiency at scale, drastically reducing data retrieval latencies and ensuring cross-service transactional consistency.
- Spearheaded continuous improvement in development processes, designing comprehensive unit and integration testing frameworks that drove test coverage from 50% to over 90% via JUnit, Spock, and Mockito.
- Partnered extensively with cross-functional product and data squads to define API boundaries, design interfaces, and ensure rapid, high-confidence CI/CD release cycles.
Peter S.
Last position:
Senior ML Engineer & AI Researcher at Anonymous Client
Project: Defect Generation on Test-Bench Images of Metal Surfaces Environment: Automated Visual Inspection (AVI), Metallurgy & Manufacturing
- Objective & Implementation: Designed, architected, and trained Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g., cracks, inclusions, scale) on rough metal surfaces under real test-bench lighting conditions for privacy-compliant and efficient dataset expansion (data augmentation).
- Technical Design: Implemented robust Generative AI and computer vision pipelines in Python and PyTorch. Used semantic segmentation approaches for mask-controlled defect synthesis and subsequent evaluation with EfficientDet object detection models.
- Business Impact: Massive dataset upscaling (10x) without time-consuming and costly physical test-bench runs, while significantly improving the detection performance of automated inspection systems.
Technologies & Skills Used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision
Karthikeyan R.
Last position:
Full-Stack Developer — Own Product at Self-employed
Java 21 · Spring Boot 3 · Keycloak · PostgreSQL · Docker · Nginx · GitHub Actions · DigitalOcean · React 18 · TypeScript · Plasmo
- Architected and shipped a production-ready Job Application Tracker end-to-end: REST API with 5-stage workflow, pagination, sorting, and dynamic filtering — full ownership from design to live cloud deployment on DigitalOcean.
- Implemented production-grade identity management: OAuth 2.0 / OpenID Connect / JWT / RBAC via Keycloak, applying Hexagonal Architecture and DDD principles.
- Built automated CI/CD pipeline (GitHub Actions); containerised with Docker; Nginx reverse proxy with path-based routing and SSL termination.
- Developed a Chrome Extension (Plasmo framework, Manifest V3) that auto-fills job applications directly from LinkedIn into the tracker — demonstrates full product thinking across backend API and browser client.
Discover over 15,000 top freelancers
Statistics of experts using AWS Lambda
Aggregated from the professional profiles of matched freelancers.
Experience
16 years

Position duration
2.1 years

Positions per freelancer
11

Top business areas
Information Technology, Product Development, Business Intelligence

Top industries
Information Technology, Banking and Finance, Automotive

Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
93%
Master's degree or higher
61%
Doctorate
9%

Certifications per freelancer
3

Most common languages
English, German, French

Speak two or more languages
99%
Based on our profile pool as of 11 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 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 11 Nov 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 (96%)
- Banking and Finance (47%)
- Automotive (43%)
- Retail (37%)
- Education (33%)
- Professional Services (32%)
- Energy (28%)
- Healthcare (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Serverless foundation
AWS Lambda is a managed compute service that runs code in response to events without requiring a company to provision or maintain servers. It suits short-lived, independent workloads such as API handlers, file processing, scheduled jobs and automation. Teams pay attention to execution behavior, permissions, observability and response time rather than operating a fixed fleet.
Where Lambda fits
Lambda functions often sit behind Amazon API Gateway or an Application Load Balancer and react to events from S3, DynamoDB, EventBridge, SQS and SNS. They can support web and mobile backends, data pipelines, notification services and internal automation. A sound design keeps functions focused and uses queues, retries and dead-letter handling to control failure paths.
Ecosystem and tooling
Professionals work across the AWS ecosystem and choose tools that make deployments repeatable.
- Define infrastructure with AWS CDK, AWS SAM, CloudFormation or Terraform
- Package functions with runtimes, layers, containers and dependency controls
- Connect workflows through EventBridge, Step Functions, SQS and SNS
- Monitor logs, traces and metrics with CloudWatch and AWS X-Ray
When companies need help
Companies usually bring in freelance expertise when a serverless initiative must move from a prototype to a reliable production system. Specialists can untangle slow cold starts, excessive permissions, duplicate events, weak test coverage or unclear ownership between functions. They also help migrate selected workloads from long-running services when Lambda offers a better operational fit.
- Review an existing Lambda architecture and its AWS account setup
- Create secure event flows and resilient asynchronous processing
- Improve deployment pipelines, testing and release controls
- Establish cost, logging and incident-handling practices
Skills that matter
Strong AWS Lambda professionals understand more than function code. They know IAM, networking, API design, data modeling and distributed-system behavior, including idempotency, concurrency limits, retries and eventual consistency. Useful adjacent experience includes TypeScript, Python, Java, Go or .NET, plus CI/CD and infrastructure as code.
What good delivery looks like
Quality work starts with clear boundaries, least-privilege access and a deliberate choice between synchronous and asynchronous execution. A specialist should explain timeout, memory, concurrency and retry decisions, then validate them with tests and production-like observability. They should also document event contracts, failure handling and the point at which a container or continuously running service would be a better choice.
Frequently asked questions
Not sure where to start with AWS Lambda? These answers cover the essentials.
AWS Lambda runs code in response to events, HTTP requests, schedules or messages. Companies use it for serverless APIs, file and data processing, workflow steps, notifications, integrations and operational automation without managing application servers.
AWS Lambda removes server and cluster management for event-driven workloads and scales execution automatically within configured limits. Containers or traditional services can be a better fit for long-running processes, stable workloads, specialized operating-system needs or applications that require extensive runtime control.
A strong AWS Lambda specialist commonly works with API Gateway, IAM, S3, DynamoDB, EventBridge, SQS, SNS, Step Functions and CloudWatch. They should also understand networking, infrastructure as code, CI/CD and the application runtime used by the project.
The right level depends on the system’s risk and integration depth, not on a fixed tenure. A small function may need focused implementation skills, while a production platform needs someone who can design event contracts, secure IAM policies, manage retries and concurrency, and operate the system after release.
AWS Lambda is well suited to remote work because its architecture is defined through source code, infrastructure configuration, tests and observable deployments. Remote collaboration works best when the team documents event schemas, access boundaries, environments, review rules and ownership of AWS accounts.
Ask how the specialist handles idempotency, retries, dead-letter queues, cold starts, permissions and partial failure. Review architecture diagrams, deployment practices, test strategy and monitoring choices rather than judging only whether a function works in a local example.
AWS Lambda is not a universal replacement for continuously running backends. It is strongest when work can be triggered by events and divided into manageable units; applications with persistent connections, heavy sustained computation or strict runtime control may suit containers or managed services better.
Common problems include overly large packages, broad IAM permissions, duplicated event handling, hidden retry behavior and functions that do too much. Experienced AWS Lambda professionals address these issues with smaller boundaries, least privilege, structured logs, contract tests and explicit failure paths.
The average hourly rate of freelancers who have used AWS Lambda in their recent projects is 94 €, which corresponds to a daily rate of about 753 € based on an 8-hour working day.
Of the freelancers who have used AWS Lambda in their recent projects, 93% hold at least a Bachelor's degree, 61% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers who have used AWS Lambda in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers who have used AWS Lambda in their recent projects are English (99%), German (98%), and French (12%).
The most common industries among freelancers who have used AWS Lambda in their recent projects are Information Technology (96%), Banking and Finance (47%), and Automotive (43%).
The most common business areas among freelancers who have used AWS Lambda in their recent projects are Information Technology (100%), Product Development (87%), and Business Intelligence (49%).
Main locations of FRATCH Experts, who have recently used AWS Lambda
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
In Austria our freelancers and interim experts support companies from Vienna to Graz — on-site where your project needs them, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Countries:
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