Argo Workflows Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Argo Workflows
Deepak Mishra
Last position:
Lead ML Platform Engineer at Billie GmbH
- Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
- Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
- Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
- Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
- Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
- Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
- Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
- Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
- Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
- Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices
Marco Lindner
Last position:
Senior IT Consultant | Cloud Data Engineer | Infrastructure Architect at Hannover Rück SE
Built an enterprise data lakehouse platform on Azure Databricks
Developed production data pipelines and governance structures
Implemented private cloud infrastructures using Terraform
Introduced modern CI/CD standards in Azure DevOps
Implemented secure IAM and governance concepts
Developed scalable PySpark and Delta Lake frameworks
Supported self-service analytics and data product approaches
Provided architecture and platform consulting for enterprise data initiatives
Built a central DataHub architecture for insurance data
Integrated multiple subsystems into a lakehouse platform
Introduced data governance and data lineage
Supported modern analytics and reporting standards
Optimized data delivery for business and analytics teams
Olaf Radicke
Last position:
DevOps Architect / Consultant at Authority with increased security requirements
- Identification of requirements (legal, organizational, and technical)
- Design of solution architectures
- Evaluation of concepts and technologies
- Preparation of decision templates
- Architectural Decision Records (ADR)
- Coordination of implementation
- Review of implementations
- Documentation
Vitaliy Ryumshyn
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.
Sebastian Striebig
Last position:
Group Product Manager – Digital Platform Discovery at SPREAD.AI
- Developed and implemented organization-wide discovery framework based on Ulwick’s Outcome-Driven Innovation; enabled 7 Product Owners to systematically identify and quantify unrealized value through shared outcome language and opportunity scoring methodology
- Transformed Product Owner role from backlog clerks to strategic experimenters; established dedicated time budget for autonomous hypothesis testing and discovery activities
- Rebuilt customer journey maps to start at actual user need (tool selection phase) instead of platform entry point; eliminated manual data aggregation work previously done by project teams
- Implemented OKR framework across 4 product teams; defined quarterly objectives with measurable key results (e.g., 40% reduction in manual integration effort, self-service adoption increase)
- Unified 3 separate platform roadmaps through cross-team dependency mapping and shared service agreements
- Supported enterprise sales cycle with ROI modeling and technical due diligence for automotive and defense customers
Oluwasegun Adebayo
Last position:
Observability Specialist at ING GmbH
- Requirements analysis for the enterprise-wide observability platform.
- Creation of playbooks and pipelines for rolling out Envoy, OpenTelemetry Collectors, and OpenTelemetry Agents.
- Conducting load tests for capacity planning of metrics for the observability platform.
- Documentation and implementation of compliance standards for production readiness.
- Creation and design of RED metrics, spanmetrics, JBoss, and Tomcat dashboards for mission-critical applications.
- Setting up alerts for critical applications for proactive incident response.
- Integration of OpenShift applications into the enterprise-wide observability stack.
Ales Loncar
Last position:
Senior DevOps Consultant (Freelance) at European Union Agency (via IBM)
- Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
- Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
- Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
- Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
- Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
- Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
- Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
- Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
- Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
- Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.
Gyan Prakash
Last position:
Senior DevOps and Cloud Architect at Bosch
- Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
- Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
- Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
- Contributed to hiring and technical interviews as part of the recruitment panel.
Jonathan Krauß
Last position:
Test Automation Engineer (Freelancer) at Bank Verlag GmbH
- Refactoring test automation (Java/Kotlin)
- Implementing integration tests (Cucumber, Gherkin)
- Bug fixing and implementing new features in pair programming
- Implementing test processes in CI/CD architecture (GitLab)
- Planning and creating a test strategy
- Analyzing business processes to assess test coverage
- Bug tracking and verification (Kubernetes/k8s, Kibana)
- Extending the deployment pipelines in GitLab CI
- Evaluating logs and metrics
- Implementing tests to verify security requirements (PCI DSS/ISO 27001)
Andreas Steffan
Last position:
Lead Developer at Software
- Extended the document management system with a standard CMIS (Content Management Interoperability Services) interface
- Implemented CMIS core services like navigation, access rights, search, CRUD operations, and versioning in Java
- Implemented based on RESTful / OpenAPI services
- Delivered as a fat-jar and native container image
- Deployed on-premises and serverlessly as an Azure Container Application using Terraform
- Improved team autonomy through infrastructure engineering and short feedback loops
- Established observability with OpenTelemetry, Azure Monitor, and Azure Logic Apps
- Introduced Terraform and trunk-based development processes
- Ensured quality with BDD tests in C# using SpecFlow and Testcontainers
- Created Azure DevOps pipeline integration tests
- Introduced cloud deployment processes
- Trained staff in cloud and Terraform
Torsten Glunde
Last position:
Datavault with Informatica on Oracle at SEFE
- Datavault modeling and performance improvements in Oracle.
- Requirements process with model-driven Datavault automation.
- Preparation of business requirements for the pricing database in the gas and electricity market.
- Sales performance based on Salesforce CRM.
- Tasks: design and development.
- Tools used: Informatica, Oracle, DBT, Docker, DataOps, Airflow Workflow, Python Ingestion, Gitlab CI.
Pit Wegner
Last position:
Devops & Site Reliability Engineer at Alpin Analytics GmbH
- Planning and building a multi-tenant data analytics platform based on bare metal Kubernetes
- Designing a cloud native data ingest architecture incorporating Argo Workflows and Argo Events
- Technologies and tools: Kubernetes, Docker, Helm, Argo Workflows, Argo Events
Discover over 15,000 top freelancers
Statistics of experts using Argo Workflows
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
1.7 years
Positions per freelancer
12
Top business areas
Information Technology, Operations, Product Development
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Operations, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
57%
Certifications per freelancer
3
Most common languages
German, English, French
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 Germany 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 Germany using Argo Workflows
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
Workflow automation
Argo Workflows is a Kubernetes-native engine for running complex jobs as declarative workflows. It is used for batch processing, CI and CD steps, data pipelines, and repeatable application tasks. Teams choose it when they need clear control over dependencies, retries, and parallel execution.
Common use cases
- Build multi-step delivery pipelines on Kubernetes
- Run data and machine learning workflows
- Orchestrate image builds, tests, and releases
- Schedule repeatable operational jobs
- Trigger workflows from events or APIs
Argo Workflows, often shortened to Argo, fits teams that want workflow control close to the cluster. In Germany, it is common in software, manufacturing, logistics, and data-heavy businesses that need strong automation and predictable execution.
Ecosystem and tooling
A strong specialist works with the wider Argo stack, including Argo CD, workflow templates, artifact handling, and Kubernetes primitives such as pods, namespaces, and service accounts. They also understand container images, secrets, RBAC, observability, and Git-based delivery patterns.
What strong experts do
Strong professionals keep workflows readable and stable. They structure templates well, reduce duplicate logic, set proper retries and timeouts, and make logs, artifacts, and parameters easy to inspect. They also know when to use Argo Workflows instead of a simpler CronJob or a heavier external orchestrator.
When to bring in freelance help
Companies bring in freelance expertise when a workflow setup is failing, hard to maintain, or too tied to one team. They also need help when they are moving orchestration onto Kubernetes, standardizing pipelines across products, or integrating Argo with existing delivery and data tooling.
Hiring for Germany
For teams in Germany, freelance specialists are often a good fit for remote discovery, implementation, and handover. On-site work only becomes useful when workflow design depends on local infrastructure, cross-team workshops, or tight coordination with platform and operations specialists. Clear documentation in English is usually expected.
Frequently asked questions
What clients ask us most about Argo Workflows — answered in short.
Argo Workflows is used to run multi-step jobs on Kubernetes with clear control over order, branching, retries, and artifacts. Companies use it for delivery pipelines, batch processing, data preparation, and other repeatable tasks that need reliable execution. It is a good fit when simple scripts are no longer enough.
Argo Workflows runs jobs and workflow steps, while Argo CD manages Git-driven application delivery to Kubernetes. Many teams use both, but they solve different problems. If you need orchestration of tasks, workflows is the right focus; if you need cluster state sync, look at Argo CD.
Argo Workflows is usually the better fit when the work already lives in Kubernetes and the steps are container-based. Airflow is often chosen for broader scheduler-style data orchestration, especially when teams want a Python-first model. The decision depends on your runtime, not just the feature list.
A strong Argo Workflows specialist should understand Kubernetes, container images, YAML, CI and CD practices, and access control. Experience with Helm, GitOps, observability, and secret handling is also valuable. For data-heavy use cases, cloud storage and artifact management matter too.
A good Argo Workflows freelancer can add value quickly if the workflow goals, cluster setup, and deployment path are clear. For larger programs, they should also understand naming rules, environment promotion, failure handling, and who owns each step. The more existing automation you have, the more important good documentation becomes.
Yes. Argo Workflows work is often remote-friendly because most tasks happen in code, manifests, and cluster configuration. For teams in Germany, remote collaboration usually works well when there is a shared backlog, clear language expectations, and fast access to the cluster and logs.
Look for Argo Workflows professionals who can explain why a workflow is structured a certain way, not just how to write it. Good signs are clean templates, sensible retries and timeouts, clear artifact handling, and awareness of Kubernetes limits. They should also show how they test and debug failures.
Argo Workflows becomes hard to maintain when templates are copied too often, parameters are unclear, and ownership is scattered. Debugging also gets painful when logs, artifacts, and retry rules are inconsistent. A strong specialist cleans up the workflow design before adding more steps.
The average hourly rate of freelancers in Germany who have used Argo Workflows in their recent projects is 109 €, which corresponds to a daily rate of about 872 € based on an 8-hour working day.
Of the freelancers in Germany who have used Argo Workflows in their recent projects, 100% hold at least a Bachelor's degree and 57% hold at least a Master's degree.
On average, freelancers in Germany who have used Argo Workflows in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Germany who have used Argo Workflows in their recent projects are German (100%), English (100%), and French (17%).
The most common industries among freelancers in Germany who have used Argo Workflows in their recent projects are Information Technology (92%), Banking and Finance (75%), and Automotive (50%).
The most common business areas among freelancers in Germany who have used Argo Workflows in their recent projects are Information Technology (100%), Operations (75%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Argo Workflows
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 Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
