
Elasticsearch Expert in Berlin
for search, analytics and AI-matched freelance supportHire experts who design relevance-driven search, build resilient indexing pipelines and connect Elasticsearch with cloud data systems. FRATCH matches you quickly with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Berlin, who have recently used Elasticsearch
Alois R.
Last position:
Senior Fullstack Developer at brandung GmbH
- Opt-in RAG extension over tenant-owned data sources (SharePoint, Confluence) on existing multi-tenant enterprise AI platform
- Architecture: ADRs, solution evaluations, permission strategy, cost modeling
- End-to-end SharePoint and Confluence connectors: OAuth consent flows, token refresh, metadata sync, search integration
- Permission resolution: ACL indexing at ingestion and query-time verification (document-level security)
- Elasticsearch hybrid search (semantic + keyword) with RRF scoring
- RAG chat with context injection and source citations
- Stack: Elastic Cloud, Elasticsearch, Docker, Northflank, Next.js, React, TypeScript, Prisma, Microsoft Graph API, Atlassian REST API, OAuth 2.0
Imran A.
Last position:
Software Engineer II at LivePerson Germany GmbH
- Led development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
- Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
- Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
- Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
- Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
- Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.
Rüdiger S.
Last position:
Full-Stack Software Engineer / Consultant for Digitalization at ARTEVENT
Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.
Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.
Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.
Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.
Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.
Jorge P.
Last position:
Software Engineer – AWS and Kubernetes Specialist at Citti
- Creation, maintenance and hardening of Kubernetes clusters employing Ansible and ArgoCD
- Keywords: Ansible, AWX, Kubernetes, NetApp, Prometheus, CI/CD ArgoCD, SSO, Fluent-bit, HAProxy, Calico, Keycloak, oauth2-proxy, SealedSecrets, kubeseal, Aqua kube-bench, CIS-Benchmarks, Aqua Trivy operator
Krishna M.
Last position:
Associate Product Manager at Carelon Global Healthcare LLP
- Defined and executed product vision & strategy, collaborating with UX, architecture, and engineering teams, resulting in a 30% improvement in user satisfaction across key product touchpoints.
- Owned end-to-end product lifecycle management, overseeing the launch of 5 major product updates, improving product efficiency and feature adoption by 25%.
- Defined and structured epics, features, and user stories; validated and ensured 100% of completed stories met definition of ‘Done' before release.
- Led backlog grooming, prioritization (WSJF, MoSCoW), and sprint planning, ensuring 95% on-time delivery of features in quarterly release cycles.
- Worked with technologies: API, Angular, Node, ReactNative (Mobile), SQL, Kafka, AWS cloud with ES (Elastic search) with JSON file indexes.
- Used Confluence and Jira for maintaining product details and product backlogs for 10 years.
- Used Figma, Sketch, Miro for 4 years.
- Directed cross-functional teams, coordinating with developers, designers, and business units, driving a 40% reduction in time-to-market for critical features.
- Spearheaded product release demos, UAT, and go-to-market (GTM) strategies, leading to a 15% increase in user adoption within the first quarter of launch.
- Optimized member experience on Anthem's digital health platform, resulting in a 20% increase in active user engagement and a 10% boost in member retention.
Murad H.
Last position:
Founder & Technical Lead at Hubpoint.Ai
- Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
- Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
- Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
- Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
- Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.
Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker
Domenic V.
Last position:
Founder at VOS Ventures Tech UG
Working as independent / interim / fractional CTO / engineering director, technical leader, builder, coach. Select achievements:
- Fractional CTO for a music-tech startup. Helped unlock further funding by providing the technical strategy and plan behind their vision and pitch deck, then executed it: vision to a working beta, 0 to 1, on time and on budget against that plan.
- AI automation for a compliance business. An annual research process — days of a person working through spreadsheets and checking websites by hand, so costly it had been abandoned for years — now runs automatically every month and takes about an hour to review. Stale or missing data became current data, twelve times a year.
- An AI development autopilot. Agents take an approved ticket, implement test-first, verify against a running system and open a pull request. An AI committee reviews on various categories and provides risk assessments based on my specs. Nothing merges without a human.
- Coaching and sparring for engineering leaders. Developing engineering managers was most of my job as a director; I now do it one to one.
Wolfram K.
Last position:
AI / Machine Learning Engineer (Projects & Applied AI) at UNIVERSITÉ PARIS 1 PANTHEON-SORBONNE & LIORA
- Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
- Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
- Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
- Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
- Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow
Nune I.
Last position:
Fractional CTO at OpsWorker
OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.
Nikunjkumar P.
Last position:
Senior Java Backend Developer at Questax Professionals GmbH
- Provide the Price Listing Service team with prices for all cars and vans in different markets
- Adapt market-specific requirements such as taxes, government subsidies, campaigns
- Import and synchronize new prices for all new and existing cars and store them in the Redis datastore
- Support our product and on-call duty
- Daily business, development of new features, bug fixing
- Pair programming, code review, mob programming
- Develop POCs for new ideas
- Maintain and extend the backend
- DevOps tasks
- Run Kubernetes updates
- Adjust and further develop Kubernetes resources
- Develop and adapt Helm charts
- Adapt and update ArgoCD
- Maintain, adapt, and improve CI/CD
Olaf T.
Last position:
CTO, Shareholder, Agile Coach, Product Owner at fluidx digital GmbH
- Development and rollout of a browser-based platform for camera streaming, augmented reality (AR), and visual computing
- Device-independent camera streaming for smartphones, tablets, desktop PCs, as well as VR and AR headsets
- Ensuring GDPR-compliant hosting in Open Telekom Cloud and other sovereign cloud providers
- Intuitive visual and collaborative features to increase efficiency and integrate smoothly into existing business software
Louis G.
Last position:
Freelance Solutions Architect and Machine Learning Engineer at Self-employed
- Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
- Work with customers to understand their challenges and provide the best solutions based on open-source data products
- Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
- Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
- Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
- Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
- Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
- Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible
Qaiser A.
Last position:
Freelance Lead DevOps Engineer at Schwarz Gruppe Produktion
Bootstrapping a CloudOps team and building a multi-cloud provider backend for a low-code Internal Developer Platform (IDP) with env zero
Introducing user story mapping, ADRs, milestones, and backlog management
Designing and developing core APIs, setting up CI/CD pipelines, OpenTofu/Terraform scripts
Representing and communicating the team with third-party stakeholders (e.g. env zero)
(Cross-)team coaching on DevOps, software design, Terraform, Golang, and agile practices
Hans-Christian P.
Last position:
Senior Full Stack and AI Engineer at simpleshow
- Developed a Generative AI-based image recommendation engine for an AI video production system
- Implemented automatic image analysis with GPT-4o
- Built semantic vector search using OpenAI embeddings, MongoDB, and OpenSearch
- Tagged and indexed 4 million customer assets
- Redeveloped recommendation engine with a hybrid, balanced keyword and vector search plus filters
Frank B.
Last position:
Software Engineer at Freelancer
- Freelance Software Engineer with a focus on backend (Python/Django) and frontend (VueJS).
Discover over 15,000 top freelancers
Statistics of experts using Elasticsearch
Aggregated from the professional profiles of matched freelancers.
Experience
18 years

Position duration
2.3 years (Germany: 2 years)

Positions per freelancer
11 (Germany: 12)

Top business areas
Information Technology, Product Development, Business Intelligence

Top industries
Information Technology, Media and Entertainment, Retail

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
96% (Germany: 93%)
Master's degree or higher
46% (Germany: 50%)

Certifications per freelancer
2

Most common languages
German, English, French

Speak two or more languages
97% (Germany: 99%)
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 Berlin 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 Berlin 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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Elasticsearch 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 (97%)
- Media and Entertainment (48%)
- Retail (42%)
- Automotive (36%)
- Banking and Finance (36%)
- Education (33%)
- Healthcare (27%)
- Energy (24%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Search and discovery
Elasticsearch is a distributed search and analytics engine built on Apache Lucene. It indexes structured and unstructured data so applications can return relevant results, filter large collections and explore information in near real time. Companies use it for product search, log analysis, observability, security monitoring and content discovery.
Core capabilities
Professionals work with mappings, analyzers, tokenization, relevance scoring and aggregations. They design index strategies that support both precise filters and natural-language queries, while managing refresh behavior, shard layouts and document modeling. Elasticsearch can also support vector search and hybrid retrieval for modern recommendation and AI-assisted search experiences.
Ecosystem and tooling
The wider Elastic Stack includes Kibana for visualization, Logstash for data processing and Beats for lightweight collection. Strong specialists also use Elastic APM, Elastic Agent, ingest pipelines, snapshots and REST APIs. Depending on the environment, they connect Elasticsearch with Kafka, cloud storage, relational databases, Kubernetes or application services written in common backend languages.
Where it fits
- Build product, catalog and marketplace search
- Centralize application logs and infrastructure events
- Create dashboards for operations, security and business analysis
- Add autocomplete, faceting, highlighting and typo tolerance
- Combine keyword retrieval with vector-based similarity
When companies need support
Freelance expertise is useful when search quality is poor, indexes grow unpredictably or a migration has to happen without disrupting users. Companies also bring in specialists to replace fragile logging setups, tune costly clusters or connect Elasticsearch to a new data pipeline. In Berlin, remote delivery is common, while workshops and stakeholder sessions may still benefit from on-site collaboration.
What strong specialists deliver
A capable professional starts with query and data requirements rather than defaulting to a cluster design. They explain trade-offs around mappings, shard sizing, replicas, refresh intervals, retention and access controls, then validate decisions with representative data. Look for clear documentation, repeatable deployments, monitoring, failure testing and a plan for relevance evaluation. Experience with German and English-speaking stakeholders can also help Berlin teams working across locations.
Frequently asked questions
Before you brief your next project: the most common questions about Elasticsearch.
Elasticsearch is commonly used for fast full-text search, filtering, log analytics and observability. It can index product catalogs, documents, events and application data, then expose results through relevance-ranked queries and aggregations.
Elasticsearch is optimized for distributed search and analytics rather than transactional integrity. A relational database remains the system of record for many applications, while alternatives such as OpenSearch, Solr or managed cloud search services may be considered based on licensing, operations, compatibility and search requirements.
A strong Elasticsearch specialist usually understands data modeling, REST APIs, Linux, containers and at least one application language. Useful adjacent skills include Kafka, Logstash, Kibana, Kubernetes, cloud infrastructure, observability and security controls.
The right level of Elasticsearch experience depends on the risk and scope, not a fixed timeline. A simple index or query improvement may need focused expertise, while a migration, multi-region cluster or relevance program requires someone comfortable with architecture, operations and failure recovery.
Elasticsearch projects are often suitable for remote collaboration because configuration, query testing and monitoring can be handled through shared environments. Berlin teams may still prefer on-site sessions for search workshops, incident reviews or close coordination with product and data teams.
Elasticsearch supports vector search and can combine semantic retrieval with keyword matching, filters and ranking logic. The quality of the result depends on embedding choices, document preparation, index design and evaluation against real user queries.
A reliable Elasticsearch engagement should produce documented mappings, query logic, deployment settings and monitoring signals. Depending on the scope, deliverables may also include migration steps, backup and restore procedures, load tests, relevance checks and clear runbooks for incidents.
Ask a Elasticsearch professional to explain how they would model the data, test relevance and handle shard growth before discussing specific settings. Good specialists connect technical decisions to user behavior, measure results with representative queries and communicate operational risks without hiding behind default configurations.
The average hourly rate of freelancers in Berlin, Germany who have used Elasticsearch in their recent projects is 99 €, which corresponds to a daily rate of about 790 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Elasticsearch in their recent projects, 96% hold at least a Bachelor's degree and 46% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Elasticsearch in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Berlin, Germany who have used Elasticsearch in their recent projects are German (97%), English (97%), and French (18%).
The most common industries among freelancers in Berlin, Germany who have used Elasticsearch in their recent projects are Information Technology (97%), Media and Entertainment (48%), and Retail (42%).
The most common business areas among freelancers in Berlin, Germany who have used Elasticsearch in their recent projects are Information Technology (100%), Product Development (97%), and Business Intelligence (48%).
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.
Countries:
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