Datadog Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Datadog
Thomas Hoefkens
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
- Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
- Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
- Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
- Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
- Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
- Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integration of RESTHeart to create a REST API for MongoDB.
- Build an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).
Tobias Nawa
Last position:
Enterprise & Solutions Architect
- Building an independent enterprise IT setup — cloud strategy, network, AWS landing zone, security requirements, contract negotiations.
- Migration of all applications; avoiding high contractual penalties for the client.
- Onboarding and coordination o...
Pooja Kumar
Last position:
Product Owner at Celonis
An enterprise process mining and execution management platform that helps organizations analyze, visualize, and optimize their business processes using event data.
- Aligned 40+ engineering squads across 5 countries to deliver platform capabilities at scale, driving release infrastructure, change management, and rollout governance with zero post-launch defects for 1000+ enterprise customers
- Owned celonis studio platform roadmap prioritization, balancing technical investments, commercial priorities, and operational needs, driving 50%+ market share growth against legacy products
- Translated requirements into specifications, architectural decision records, and delivery plans in collaboration with engineering and UI/UX, resulting in a 20–30% increase in user engagement
- Drove the GA launch strategy, running pilot programs and customer discovery sessions to validate operational readiness and enterprise adoption
Enis Spahi
Last position:
Software Developer at 50Hertz Transmission GmbH
- Participated in the gradual modernization of components into cloud-native 12-factor applications.
- Worked closely with the business operations team to eliminate manual processes and resolve several performance bottlenecks.
- Designed and implemented a CI/CD pipeline to increase developer productivity, enforce quality and security checks, and automate product delivery.
- Migrated several components into the OpenShift Kubernetes cluster.
- Built a monitoring stack from scratch with Prometheus and Grafana to monitor services running in OpenShift.
- Developed dashboards in both Grafana and Splunk for operational transparency.
- Implemented an OIDC/OAuth2-based single sign-on (SSO) solution with Keycloak to secure multiple applications.
- Technologies: Java, Spring, Quarkus, Kafka, MySQL, Cassandra, Redis, Spring Data, Hibernate, Docker, Kubernetes, OpenShift, Keycloak, OIDC, OAuth2, Helm, Prometheus, Grafana, Splunk, Spark.
Piotr Kuczyński
Last position:
Senior Software Engineer at On
- Built middleware service integrating EDI providers and marketplace partners with Microsoft Dynamics 365 to receive sales orders and communicate shipments, invoices, inventory, and price catalogues
- Utilized a mixture of REST APIs and event-driven data processing pipelines
Alexandru Gunescu
Last position:
Head of Cloud Infrastructure at BP
- Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
- Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
- Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
- Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
- Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
- Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
- Supported development and maintenance of IT strategy aligned with business requirements
- Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
- Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
- Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
- Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
- Developed a two-year infrastructure technology roadmap yielding 25% cost savings
- Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics
Maziyar Khorrami
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Alexander Nagy
Last position:
Security Expert at DAK-Gesundheit
- Pentesting of mobile applications
- Code review
- Gematik audit
- Development of secure software development methods
- Creation of security and test concepts
- Penetration testing of software and architecture
- Vulnerability analysis
- Automation and information security
- Use of Confluence and Jira
- Working with databases, J2EE, JavaServer Faces, Liquibase, Apache, Maven, Mercurial, Oracle Financials
- Documentation and creation of security policies
- Management of software systems, SharePoint, PrimeFaces, Git
- Compliance with security regulations and .NET, AWS, API
- Tools: MobSF, Frida, Android Studio, Drozer, Objection, Azure
Jiri Sostok
Last position:
Quality Manager/Test Management at Noriba GmbH
- Creation of test concepts
- Development of test processes
- Coordination of test case development: stress tests, functional tests, performance tests, high data rate tests, integration tests, etc.
- Hardware testing: FPGA, RF
- Test automation and regression testing
- Ensuring 24/7 operation of the test system
- Analysis & reporting
- Regular coordination of the test team, meetings with other stakeholders
- Communication and coordination with stakeholders and project managers
Christof Nasahl
Last position:
Senior Developer at Otto GmbH
- Further development of personalized advertising spaces on the Otto web shop
- Full-stack development in a Kanban-driven team of about 15 people
- Technologies: Microservices, Kotlin, Spring, Spring Boot, Gradle, MongoDB, HTML, JS, Node, SCSS, AWS
- Development process: Kanban; continuous integration with AWS CodePipeline and GitHub Actions
Mario Brajkovski
Last position:
Site Reliability Engineer at Joyn GmbH
- Specialized in cloud infrastructure design, optimizing AWS and SaaS usage.
- Empowered development teams by ensuring security, scalability and reliability.
- Expertise included robust monitoring and automation for streamlined deployments.
- Provided technical guidance for faster releases and supported microservices principles.
- Actively participated in architecture discussions and shared critical infrastructure knowledge with development teams.
Ana Cunha
Last position:
Software Engineer - Internship at BMW
- Integrated sensor data used for lane boundary extraction into the internal fingerprint pipeline, supporting AI-based localization for autonomous vehicles using Python.
- Worked in a cloud-based environment using AWS services for data storage and processing.
- Authored onboarding and technical documentation, improving team efficiency and knowledge transfer.
- Collaborated with other engineers to translate data requirements into engineering solutions while adhering to confidentiality protocols.
Andreas Kraus
Last position:
Senior Developer at ioki GmbH, a Deutsche Bahn AG company
- Fullstack development based on Next.js and TypeScript
- Development and optimization of geospatial database queries for PostgreSQL/PostGIS
- Visualization of geospatial data using Mapbox
- Design and execution of load tests and performance optimizations
- Code reviews and documentation tasks
- Technologies: JavaScript, TypeScript, Next.js, React, Zod, tRPC, Storybooks, PostgreSQL/PostGIS, MicroORM, Knex, Material UI, Mapbox, BullMQ, Jest, Playwright, Artillery.io, K6, Sentry, Figma, GitLab, Grafana, GTFS
Discover over 15,000 top freelancers
Statistics of experts using Datadog
Aggregated from the professional profiles of matched freelancers.
Experience
19 years (Germany: 17 years)
Position duration
2.4 years (Germany: 1.9 years)
Positions per freelancer
10 (Germany: 11)
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Retail, Automotive
Certification focus areas
Information Technology, Product Development, Quality Assurance
Bachelor's degree or higher
100% (Germany: 93%)
Master's degree or higher
91% (Germany: 64%)
Doctorate
9% (Germany: 4%)
Certifications per freelancer
2
Most common languages
English, German, Spanish
Speak two or more languages
100%
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 Munich 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 Munich using Datadog
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
Observability with Datadog
Datadog is used to monitor modern systems across metrics, logs, traces, and events. It helps teams see how services behave, find bottlenecks, and track incidents before they spread. Companies use it for application monitoring, cloud visibility, and operational dashboards.
What specialists set up
- Dashboards for service health, infrastructure, and business signals
- Alert rules that reduce noise and catch real issues early
- Log pipelines, trace views, and correlated troubleshooting paths
- Cloud integrations for AWS, Azure, GCP, Kubernetes, and containers
- Synthetic checks and SLO reporting for critical user journeys
Where it fits
Datadog often sits between engineering, operations, and security work. In Munich, it is common in software teams, SaaS companies, e-commerce, manufacturing, and regulated environments that need clear service visibility. Strong experts know how to shape the setup around the system, not the other way around.
Why companies bring in freelancers
Teams usually need freelance support when they are rolling out Datadog for the first time, cleaning up noisy alerts, or merging several monitoring setups after a platform change. They also bring in specialists for incident review, dashboard redesign, log cost control, and better tracing across distributed services.
Skills that matter
A strong Datadog professional understands how metrics, logs, traces, and tag design work together. They can read service maps, tune monitors, and explain what matters to both technical and non-technical stakeholders. Familiarity with cloud platforms, containers, and CI/CD helps them deliver faster.
Good project outcomes
The best work leaves teams with dashboards they trust, alerts they act on, and a monitoring model that stays maintainable. That can include better on-call workflows, cleaner service naming, and documentation that makes future changes safer. Good experts make Datadog useful day to day, not just visible on paper.
Frequently asked questions
Quick answers to the questions that come up most around Datadog.
A strong Datadog specialist helps teams watch applications, infrastructure, and cloud services in one place. They usually build dashboards, alerts, log views, and trace paths so incidents are easier to spot and faster to explain. The goal is clear operations, not just more charts.
No. Datadog is often used for infrastructure monitoring, log management, distributed tracing, and synthetic checks as well. Many teams also use it for incident response and SLO tracking, especially when services run across cloud and container platforms.
Datadog is a managed observability suite, while Prometheus and Grafana are often assembled into a more manual stack. That makes Datadog attractive when a team wants faster setup, unified views, and less tool stitching. The trade-off is that good configuration still matters a lot.
A solid Datadog expert usually knows cloud platforms, Kubernetes, containers, and basic incident response patterns. Experience with logging, tracing, CI/CD, and tagging strategies is also valuable. If security monitoring is in scope, familiarity with cloud security signals helps too.
Simple monitoring cleanup can be handled by a specialist with focused Datadog work and good cloud knowledge. Broader projects, such as multi-team observability design or noisy production environments, benefit from someone who has worked through several rollouts. The harder the system, the more you want someone who has seen real incidents.
Yes. Datadog work is often done remotely because most tasks are configuration, review, and troubleshooting in cloud systems. In Munich, on-site time only becomes important when teams want close workshops, incident reviews, or direct work with local stakeholders. English is often enough, though German can help in mixed internal teams.
Look for clear explanations, not just feature lists. A good Datadog professional can explain why a monitor exists, how tags are structured, and how the setup reduces noise or improves incident response. Ask for examples of dashboards, alert tuning, log correlation, and tracing decisions they have made before.
If alerts are noisy, dashboards are hard to trust, or different teams see different versions of the same problem, Datadog support can help. It is also a good time to bring in a specialist when you are moving to microservices, adopting Kubernetes, or centralising monitoring across several environments. Those projects need structure early.
The average hourly rate of freelancers in Munich, Germany who have used Datadog in their recent projects is 103 €, which corresponds to a daily rate of about 828 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Datadog in their recent projects, 100% hold at least a Bachelor's degree, 91% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Munich, Germany who have used Datadog in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Munich, Germany who have used Datadog in their recent projects are English (100%), German (85%), and Spanish (15%).
The most common industries among freelancers in Munich, Germany who have used Datadog in their recent projects are Information Technology (100%), Retail (46%), and Automotive (38%).
The most common business areas among freelancers in Munich, Germany who have used Datadog in their recent projects are Information Technology (100%), Product Development (85%), and Project Management (69%).
Main locations of FRATCH Experts, who have recently used Datadog
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 Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
