Elasticsearch Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Elasticsearch
Karen Manukyan
Last position:
Personal AI Engineering Project — Croky AI at Crocky AI
Product:
- Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
- Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
- Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
- Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
- Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.
Agent Orchestration & RAG Systems
- Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
- Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.
Christiane Neher
Last position:
Management Consultant at Christiane Neher Management Consulting
Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:
- Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
- Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
- Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
- Conceptual support for the development of an integrated reporting and performance management setup
- Execution of customer insights analyses to identify patterns and anomalies within customer data clusters
Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:
- Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
- Strategic-operational consulting for the introduction of RELEX including best practices
- Support in defining overarching goals and requirements (2-year target picture)
- Guidance in scoping a relevant supply chain network segment for the project
- Development of a roadmap for iterative, incremental RELEX setup and rollout
- Assessment of project dependencies (interfaces, configurations, etc.)
- Advice on prioritized implementation of business requirements and data interfaces
- Support in test planning (data validation, system testing, UAT)
- Consulting on internationalization, change management, training, and knowledge transfer
- Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX
Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:
- Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
- Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
- Proposal of quality improvements for program and modernization efforts
- Sparring partner and professional, technical, structural and organizational consulting for project and program management
Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:
- Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
- Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
- Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
- MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)
Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:
- Coaching of the core team with topic managers and team leads
- Introduction to the OKR topic and setup of the OKR cycle
- Establishment of the OKR approach in teams and on a cross-team level
Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:
- Analysis of current challenges
- Definition of overarching goals
- Development of a proposal for a new team structure
- Identification of required competencies, skills and responsibilities
- Advisory and alignment on communication and change management strategy
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).
Srinivasu Kakaraparti
Last position:
Atruvia
Project: Tax Exemption Order Application
The client has an existing application for creating and maintaining tax exemption orders for end customers; design and implementation of a comparable application for internal employees.
- Design and implementation of microservices and the UI for the business area "tax exemption orders" using Domain Driven Design as well as Spring Boot and Angular.
- Implementation of reactive, non-reactive, and asynchronous APIs (Spring REST, WebFlux, GraphQL).
- Development of the Angular application, including state management using Signals, RxJS Observables, and subscriptions.
- Securing the API and the application using OAuth2, JWT, and OpenID Connect.
- Configuration and setup of CI/CD pipelines with Jenkins.
- Collaboration with cross-functional teams and conducting code reviews.
Environment: Java, Spring Boot, Angular 18 & 19 (standalone, signals), RxJs, Bootstrap CSS, Vitesting, OpenShift, Istio, microservices, Kafka, Dynatrace, Jenkins, GitLab, Graylog, Sonar, Oauth2, OracleDB
Sebastian Kanzow
Last position:
Senior Lead Developer, System Architecture at AVL DITEST
- Redesign of a legacy Windows app for vehicle diagnostics as an AWS cloud application
- Creating build pipelines and conducting code reviews using Kotlin, Spring Boot, Micronaut, Jenkins, and GitHub
Michael Thomas
Last position:
Senior Freelance Software Engineer — Enterprise Software & Data Projects
- Delivered backend systems, data processing solutions, and software integrations for enterprise business applications.
- Designed and implemented API-based services connecting internal platforms with external systems.
- Built automated processing workflows to handle large-scale structured business data.
- Improved application performance by 30–50% through database optimization, caching strategies, and backend refactoring.
- Reduced manual operational effort by 40–60% by automating repetitive workflows.
- Supported production environments through troubleshooting, monitoring improvements, and continuous optimization.
- Authored technical documentation and led knowledge-transfer sessions to support long-term maintainability.
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...
Gabriele Caracausi
Last position:
Startup Mentor and Technical Advisor (Volunteer) at Faros Accelerator
- Mentoring startups about technology trends and solutions, business models, market and competition research.
Celso Kurrle
Last position:
SAP Commerce Cloud FullStack Developer at Spar
- Implementation of a GitLab CI/CD pipeline based on SAP Commerce Cloud 2211
- Development of a new B2C shop with Vue, Node and TypeScript to ensure scalability, extensibility and performance optimization
- Integration of Microsoft Azure Event Grid with SAP Hybris
- Implementation of BDD with Cucumber using Gherkin syntax to promote collaboration between development and business teams
- Support and customization of a Spartacus shop
- Technologies/Languages: Java, REST, OData, Behavior Driven Development (BDD), Cucumber, Node, Vue, TypeScript, Spartacus, GitLab CI/CD, Gradle, Maven, Ant, SonarQube
Christian Schulz
Last position:
Data-Scientist/AI Engineer at The Marcom Engine GmbH & Co. KG
- Concept creation and implementing AI Agents in AWS Cloud
- Continuously alignment with stakeholders
- Collaborate with DevOps
- Technologies: Git, CI/CD (GitHub Actions), Python/ML, Streamlit, Deno/typescript, AWS SAM, AWS Bedrock, AWS Lambda, AWS Dynamo DB, AWS S3, AWS Event Bridge etc.
Michael Boldasov
Last position:
Scrum Master, Project Manager at GP Solutions DMCC
- Participated in the Riyadh Public Transport (KAPT) project introducing public transportation in Riyadh, supporting multimodal journeys combining bus, metro, car on demand.
- Worked via Thiqah and partnered with Andersen to refactor the mobile MaaS application DARB into a new microservices architecture under SCRUM framework, successfully completing Phase 1.
- Facilitated a team of 40 developers across Android, iOS, Web, Java, DevOps, architecture, analysis, and QA.
- Moderated Scrum events and communicated with the client, proactively reporting on project deadlines, scope, and challenges.
- Coordinated cross-team efforts between Thiqah specialists and GPS development teams, managing Jira and Azure DevOps trackers.
- Supported and improved Scrum processes throughout the project.
- Due to Thiqah’s takeover by Elm, subsequent phases were handled entirely in Saudi Arabia with GPS providing IT consulting.
- Tools: Azure DevOps, Jira, Confluence, Draw.IO, ChatGPT
Abhijit Ingle
Last position:
Lead Backend Developer and Architect at Gloresoft GmbH
I have worked across multiple international client projects, holding senior roles including Software Architect, Senior Software Developer, Technical Lead, and Lead Backend & DevOps Engineer. My experience spans complex enterprise environments in banking, financial services, telecommunications, engineering, and automotive domains, supporting organisations such as UniCredit Bank, Telefónica O2, and BMW.
At UniCredit Bank, within the Securities Domain Transformation program, I led the modernisation of legacy monolithic systems into cloud-native Spring Boot microservices and an Angular frontend deployed on Google Cloud Platform. Beyond implementation, I was responsible for defining the target architecture, producing system architecture diagrams and sequence diagrams, and preparing API contract documentation for clients. I designed RESTful APIs and integrated Apigee for secure and reusable cross-project service consumption of APIs. I architected Kubernetes-based deployments using Helm. CI/CD pipelines were built with Jenkins, automating code analysis using Sonar, as well as testing and deployment stages. Defining clean coding principles for the project, conducting regular code reviews, and mentoring junior developers were also among my tasks at UniCredit.
At Telefónica O2, I led the transformation of a legacy call centre desktop application into a cloud-native microservices and micro-frontend solution. I actively contributed to the platform architecture, creating system architecture diagrams, component diagrams, architecture documentation, and ADRs for future references. I improved the performance and scalability of the services. I optimised AWS infrastructure costs, particularly by minimising the use of DynamoDB and reusing test environments effectively. Observability was implemented using Prometheus, Grafana, CloudWatch, and Splunk dashboards. CI/CD pipelines were delivered using GitLab, Docker, Kubernetes, and AWS. Conducted techinical sessions for teams.
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.
Stephan Sahm
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Stephan Baier
Last position:
Freelance Data Scientist at Baier Data & AI Consulting
Discover over 15,000 top freelancers
Statistics of experts using Elasticsearch
Aggregated from the professional profiles of matched freelancers.
Experience
20 years (Germany: 18 years)
Position duration
2.6 years (Germany: 2 years)
Positions per freelancer
11 (Germany: 13)
Top business areas
Information Technology, Product Development, Operations
Top industries
Information Technology, Banking and Finance, Retail
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100% (Germany: 93%)
Master's degree or higher
75% (Germany: 48%)
Doctorate
20% (Germany: 6%)
Certifications per freelancer
2
Most common languages
German, English, Spanish
Speak two or more languages
96% (Germany: 99%)
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 Elasticsearch
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
Search core
Elasticsearch is built for fast search and analysis over large sets of text and events. Companies use it to power product search, log search, observability dashboards, and internal knowledge lookup. It is common in the Elastic Stack, often paired with Kibana and Logstash.
Typical work
- Index design and mapping
- Query tuning and relevance work
- Cluster setup, shard planning, and capacity checks
- Log and event search for operations teams
- Data ingestion pipelines with Beats or Logstash
Skills around it
Strong specialists know how documents are modeled, how analyzers change results, and how scoring affects search quality. They also understand aggregations, filters, aliases, snapshots, and upgrades. On a good project, they can explain trade-offs in plain words and keep search behavior stable as data grows.
When to bring help
Companies bring in freelance expertise when search is slow, result quality is poor, or a cluster needs rescue after growth or a risky change. The same applies when a team is adding multilingual search, alerting, or log analytics. In Munich, this often comes up in software, mobility, media, and industrial settings where search must fit existing systems and German-language content.
What strong experts do
Good professionals do more than write queries. They test analyzers, inspect mappings, watch heap and shard health, and reduce noisy alerts or irrelevant results. They also set up repeatable indexing and backup routines so Elasticsearch stays predictable under load.
Working model
Many Elasticsearch assignments fit remote work well because the main tasks are reading data flows, reviewing settings, and tuning queries. On-site support can help when teams need workshops, incident response, or coordination with local security and infrastructure groups. In both cases, clear documentation matters more than long meetings.
Frequently asked questions
What clients ask us most about Elasticsearch — answered in short.
Elasticsearch is usually used for fast search, filtering, and analytics across documents, logs, and events. Teams use it for site search, internal knowledge search, observability, security investigations, and dashboards built around the Elastic Stack.
Elasticsearch is often chosen when teams need flexible full-text search, aggregations, and log analytics in one system. Solr is also strong for search, while database search can be simpler for small use cases but usually offers less control over relevance, analyzers, and scale.
A strong Elasticsearch specialist usually knows JSON, REST APIs, data modeling, and Linux basics. Useful adjacent tools include Kibana, Logstash, Beats, and sometimes Kafka or Fluentd for ingestion. For larger setups, knowledge of Docker and Kubernetes helps as well.
Elasticsearch work varies a lot by task. Small search improvements may need only focused hands-on experience, while cluster design, upgrade planning, and incident recovery need deeper practice with mappings, shards, and performance tuning. The right fit depends on whether you need implementation, troubleshooting, or architecture input.
Yes, Elasticsearch tasks are often remote-friendly because much of the work is configuration review, query testing, and coordination with existing systems. For teams in Munich, on-site sessions can still help during workshops, migration planning, or production incidents. Many projects use a mixed setup.
Look for clear explanations of mappings, analyzers, and relevance decisions in Elasticsearch projects. Good specialists can describe how they reduced slow queries, prevented shard problems, and kept index design maintainable. Ask for examples of search or logging systems they improved and what trade-offs they made.
Elasticsearch is the search and analytics engine at the center of the Elastic ecosystem. ELK usually refers to Elasticsearch, Logstash, and Kibana, while Elastic Stack is the broader current name for that family of tools. When people say ELK, they often mean a setup built around Elasticsearch.
A Elasticsearch specialist may deliver index designs, query sets, ingestion pipelines, dashboard setups, upgrade plans, or performance fixes. In some cases they also document naming rules, retention policies, and backup routines so the setup is easier to run after the project ends.
The average hourly rate of freelancers in Munich, Germany who have used Elasticsearch in their recent projects is 95 €, which corresponds to a daily rate of about 757 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Elasticsearch in their recent projects, 100% hold at least a Bachelor's degree, 75% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Munich, Germany who have used Elasticsearch in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 2.6 years.
The most common languages among freelancers in Munich, Germany who have used Elasticsearch in their recent projects are German (100%), English (92%), and Spanish (21%).
The most common industries among freelancers in Munich, Germany who have used Elasticsearch in their recent projects are Information Technology (96%), Banking and Finance (54%), and Retail (50%).
The most common business areas among freelancers in Munich, Germany who have used Elasticsearch in their recent projects are Information Technology (100%), Product Development (96%), and Operations (46%).
Main locations of FRATCH Experts, who have recently used Elasticsearch
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.
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