InfluxDB Experts in Munich
matched in minutes from over 15,000 CVsHire experts who design InfluxDB data models, build Flux and InfluxQL queries, and connect telemetry pipelines to dashboards and alerts. FRATCH matches you quickly with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Munich, who have recently used InfluxDB
Vitaliy R.
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
Eli R.
Last position:
Technical co-founder at AskTheLaws
- Create an AI legal assistant with modern ML capabilities.
- Implement RAG architecture, with data pipelines for legal data search.
- Use AWS Bedrock for LLM and embedding models and LangChain/LangGraph
- Python with FastApi for backend and React for frontend
Majid A.
Last position:
Lead Consultant at Infosys
- Network automation
- CI/CD and Docker environment
- Python Nornir for network automation
- pyATS for monitoring and test case automation
- Network Access Control (Radius) and Device Admin Access Control (TACACS) with AAA and Cisco ISE with Cisco/HP/Aruba Devices
- Cisco ISE Clusters (2/4/8 nodes) configuration
- Cisco ISE Authentication and Authorization configuration
- Cisco/HP/Aruba Switch/WLC Tacacs/dot1x/Radius configuration
- Cisco ISE automation with Restconf and Python
Daniel C.
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Janusz M.
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Adithya B.
Last position:
Edge AI Software Engineer at Neura Robotics GmbH
- Deployed and optimized Vision-Language-Action (VLA) and diffusion policy models on NVIDIA Jetson Orin and Jetson Thor, meeting real-time inference latency targets for humanoid robot control loops.
- Built TensorRT engine pipelines (PyTorch → ONNX → TensorRT) with INT8/FP8 post-training quantization, calibration dataset design, and quantization-aware validation, reducing inference memory footprint by over 3× on Jetson without accuracy regression.
- Developed custom CUDA C++ plugins and CUDA Graphs for latency-deterministic, real-time policy execution – meeting hard runtime and memory constraints on embedded GPU targets.
- Developed an inference engine for VLA models on top of llama.cpp bringing different VLA policies under single runtime, packaging each as a single self-contained GGUF that needs no Python or PyTorch.
- Profiled and tuned GPU execution using NVIDIA Nsight Systems and Nsight Compute, identifying CUDA kernel bottlenecks, memory bandwidth saturation, and SM occupancy issues across Jetson Orin and Thor compute profiles for cross-layer performance optimization.
Discover over 15,000 top freelancers
Statistics of experts using InfluxDB
Aggregated from the professional profiles of matched freelancers.
Experience
22 years
Position duration
2.7 years
Positions per freelancer
10
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Manufacturing
Certification focus areas
Information Technology, Operations
Bachelor's degree or higher
100%
Master's degree or higher
83%
Doctorate
17%
Certifications per freelancer
2
Most common languages
German, English, Spanish
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 Munich 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 Munich using InfluxDB
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.
InfluxDB 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%)
- Banking and Finance (50%)
- Manufacturing (50%)
- Media and Entertainment (50%)
- Automotive (33%)
- Transportation (33%)
- Retail (33%)
- Telecommunication (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Time-series foundation
InfluxDB is a time-series database built for data points recorded against time. It stores measurements such as device readings, application metrics, financial signals and operational events, with tags and fields that support fast filtering and aggregation. Teams use it when recent and historical observations must remain easy to query.
What teams build
- Monitoring dashboards for infrastructure, applications and services
- Industrial IoT and machine telemetry systems
- Energy, building and environmental data pipelines
- Real-time alerting and operational reporting
- Time-based analytics for products, devices and customer activity
InfluxDB can sit behind dashboards, alerting rules and custom analytical services. Its retention and downsampling features help control storage while preserving the trends that matter.
Ecosystem and tooling
The InfluxData ecosystem includes InfluxDB Cloud, self-managed InfluxDB deployments, the Flux language and InfluxQL. Strong specialists also work with Telegraf for collection, client libraries for common programming languages, and Grafana for visualization. They connect these pieces to MQTT, Kafka, Prometheus, Kubernetes and cloud services where the wider architecture requires it.
When expertise helps
Companies often bring in freelance specialists when a metrics system is growing beyond simple dashboards. Warning signs include inconsistent measurements, expensive queries, unclear retention rules, unreliable ingestion or alerts that cannot be trusted. In Munich, local teams may value on-site workshops, while distributed projects usually need disciplined remote collaboration and clear technical documentation.
Delivery tasks
- Design measurements, tags, fields and retention policies
- Migrate data between InfluxDB versions or storage models
- Tune ingestion, cardinality, queries and resource use
- Integrate Telegraf, APIs, Grafana and alerting workflows
- Secure, monitor and operate cloud or self-managed deployments
A capable professional also defines naming conventions and checks whether the data model supports the questions the business needs to answer. They test failure handling, backfills and schema changes rather than focusing only on a working first query.
What strong specialists bring
Look for experience across data modeling, observability and production operations, not only dashboard configuration. Strong InfluxDB professionals explain trade-offs between Flux, InfluxQL and other query approaches, understand series cardinality, and can trace problems from collection to visualization. They should leave behind reproducible configuration, useful runbooks and a clear plan for future growth.
Frequently asked questions
Not sure where to start with InfluxDB? These answers cover the essentials.
InfluxDB is used to store and query time-stamped data such as application metrics, sensor readings, network measurements and operational events. Companies use it for monitoring, dashboards, alerting, IoT analytics and other workloads where time-based trends are central.
InfluxDB and Prometheus both support observability metrics, but they have different strengths. Prometheus is often chosen for pull-based monitoring in cloud-native environments, while InfluxDB suits broader time-series workloads, long-term analysis and data collected from varied devices and systems.
InfluxDB is not a general replacement for a relational SQL database. It is designed for high-volume time-series ingestion and time-based queries, while relational systems remain better suited to transactions, complex relationships and strong cross-record consistency.
A strong InfluxDB specialist should understand observability, data modeling, Linux or cloud operations and at least one client programming language. Experience with Telegraf, Grafana, Flux, InfluxQL, MQTT, Kafka or Kubernetes is valuable when the database is part of a wider telemetry platform.
The required depth depends on the workload. A small dashboard may need query and integration skills, while a production system requires expertise in cardinality, retention, backups, migrations, security and performance under sustained ingestion.
Yes. InfluxDB projects are often suitable for remote collaboration because configuration, queries, dashboards and deployment work can be reviewed through shared repositories and environments. On-site sessions in Munich can still help with sensor mapping, operational workshops or coordination across local teams.
Ask the specialist to explain a real data model, including tag choices, cardinality control, retention and query patterns. Good answers connect ingestion, storage, alerting and visualization, and include how they would test recovery, schema changes and misleading metrics.
InfluxDB Cloud reduces infrastructure management, while self-managed deployments provide more direct control over networking, storage and operations. A freelancer should be able to compare the options for data residency, connectivity, backup responsibility, scaling and the team’s ability to run the system.
The average hourly rate of freelancers in Munich, Germany who have used InfluxDB in their recent projects is 100 €, which corresponds to a daily rate of about 800 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used InfluxDB in their recent projects, 100% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Munich, Germany who have used InfluxDB in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Munich, Germany who have used InfluxDB in their recent projects are German (100%), English (100%), and Spanish (17%).
The most common industries among freelancers in Munich, Germany who have used InfluxDB in their recent projects are Information Technology (100%), Banking and Finance (50%), and Manufacturing (50%).
The most common business areas among freelancers in Munich, Germany who have used InfluxDB in their recent projects are Information Technology (100%), Product Development (83%), and Project Management (67%).
Main locations of FRATCH Experts, who have recently used InfluxDB
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.
Countries:
Berlin Hamburg 
Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 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!
Philipp Thomaschewski
FRATCH CEO
