Big Data Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Big Data
Philipp G.
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Ines L.
Last position:
UX designer for AI products at freelance
- Designing AI-first workflows that integrate AI into existing product experiences
- Developing UX concepts for prompt management, reusable and combined prompt workflows, tagging, search and information organisation
- Creating user flows, wireframes, prototypes and high-fidelity interfaces in Figma
- Defining reusable UI patterns, components and interaction logic for scalable products
- Exploring human-AI interaction patterns with emphasis on user control, transparency and manageable cognitive load
- Translating product requirements and technical constraints into developer-ready UX/UI specifications
Christiane N.
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
Damian Ś.
Last position:
CTO at FRATCH.IO
- Managed end-to-end product development, overseeing the successful delivery of technical solutions.
- Led and mentored a team of highly specialised technical professionals, fostering a culture of collaboration and innovation.
- Oversaw the hiring process to build a talented and dedicated team.
- Built a scalable and robust backend microservices system from scratch, designing and extending it to meet evolving business needs.
- Ensured the system's high availability with a 99.99% up time, implementing resilient architecture and monitoring mechanisms.
- Developed and implemented technical strategies, aligning them with business goals and objectives.
Valery K.
Last position:
Sr. Data Scientist & Engineer at Virtual Minds
- Development of high-performance ad distribution via auction
- Holistic (multi-campaign & multi-channel) advertisement placement optimization
- Algorithmic optimization for NP-Hard/NP-e
- Multiple Knapsack Problem with constraints
- Online estimation of parameters in stochastic environments
Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker
Serge K.
Last position:
MLOps (machine learning operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Christian M.
Last position:
Self-employed business consultant at CuriousMinds Unternehmensberatung
- Strategic consulting, technical consulting, interim management, and training
- Management consulting and development of application solutions through interdisciplinary solution approaches
- Employee and team development as well as innovation and communication management
Ernst H.
Last position:
Support/Development/Consulting – Process Development, E-Invoicing, XRechnung, ZUGFeRD
- Support and further development of a complex process for creating XML documents for electronic invoices / E-Invoicing (XRechnung, ZUGFeRD)
- Automation of operational processes, process development and optimization
- Development of frontend applications with MS Power Apps
- Porting SQL Server 2016 to SQL Server 2022
- SQL Server database administration
Boris A.
Last position:
Owner and Manager at UBITEQ.io
- Management of digital business
- Design, build and run solutions based on ubiquitous technologies
Christian S.
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.
Francesco D.
Last position:
Lecturer of Telematics Engineering at Polytechnic of Bari
Matthias L.
Last position:
Typescript Fullstack Engineer at Card Complete / Bank Austria
- Designed and developed the "Credit Risk Engine" using Camunda, Node.js and Typescript
- Greenfield project for credit card credit assessment for existing and new customers, including EBA KPIs, SCHUFA and CRIF scorings
- Built and modeled workflows (BPMN) and decision logic (DMN) with Camunda Modeler in close collaboration with stakeholders
- Implemented service tasks, user tasks and jobs with Nest.js, Node.js and Typescript, including exception handling
- Backend-for-Frontend (BFF), frontend with React, Tailwind and Ant Design UI library
- CI/CD with GitLab, Kubernetes/Rancher
Anton K.
Last position:
Head of Overall Technical Integration NSC / Hadoop Cloud Development at IABG
Head of overall technical integration NSC (National Secure Cloud, project with approx. 60 employees).
Technical integration of all subprojects into one product, definition of interfaces and basic components of a cloud including hardware, technical architecture of the IABG platform.
Development of a Cloud Management Platform (CMP) capable of creating private/mixed clouds of any complexity based on a textual description with one click or interactively.
CMP also includes the complete hardware management lifecycle.
Kubernetes, OpenStack and Hadoop are used as the foundation.
The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are configured automatically.
Private cloud can run any customer workloads, including a full Hadoop layer with HDFS, Spark, MapReduce, Mesos, HBase and around 20 additional ML/DL technologies.
Hadoop worker clusters can also be installed automatically without Kubernetes on bare metal or commodity hardware.
OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.
Development of a Java application Rudi: SOAP, REST, containers, DB.
Technologies: Kubernetes (K3s, Rke2, Minikube, Harbor, Gitea, Jenkins, Longhorn, Keycloak, Rancher), OpenStack (Nova, Neutron, Keystone, Swift, Ceph, Cinder, Sahara, Magnum, Kayobe, Kolla, Bigrost, Ironic), Hadoop (HDFS, Ambari, Solr, Livy, Ranger, YARN, Tez, HBase, Kafka, Hive, Zookeeper, MapReduce, Spark, Oozie, Flink), virtualization (Kubernetes (K3S), VMware, Oracle), scripting (Ansible, Puppet, Juju, Shell, Groovy, Gradle, Maven).
Arnab C.
Last position:
Consulting Partner at RibbitNova/RibbitPay
- As part of the leadership team of the crypto startup Ribbit, I am responsible for fundraising, business development, and supporting product development for Ribbit Pay
- Ribbit is developing one of the first automated, programmable, and privacy-preserving networks for recurring payments in Web3.0
Alyosh A.
Last position:
Business Intelligence Consultant at Large Private Equity Group
- Business intelligence and KPI specification and playbook for 35 European companies.
Discover over 15,000 top freelancers
Statistics of experts using Big Data
Aggregated from the professional profiles of matched freelancers.
Experience
19 years
Position duration
2.6 years (Germany: 3 years)
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
94% (Germany: 92%)
Master's degree or higher
71% (Germany: 65%)
Doctorate
19% (Germany: 17%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 19 Sep 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 Big Data
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Big Data 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 (85%)
- Professional Services (68%)
- Banking and Finance (53%)
- Education (47%)
- Manufacturing (44%)
- Automotive (35%)
- Insurance (35%)
- Media and Entertainment (35%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Big Data covers
Big Data refers to methods and systems for collecting, storing, processing and analysing datasets that are too large, fast-moving or varied for conventional tools. Teams use it to create data lakes, reporting platforms, recommendation systems, fraud detection services and machine learning foundations. The work spans batch processing, real-time events and governed access to trusted data.
Core ecosystem
The Hadoop ecosystem remains relevant for distributed storage and processing, while Apache Spark supports large-scale analytics and machine learning. Apache Kafka handles event streams, and tools such as Hive, Trino, Flink and Airflow support querying and orchestration. Cloud services, object storage, SQL, Python, Java and Scala often complete the delivery stack.
Typical project work
- Design a data lake or lakehouse with clear storage and access patterns
- Build batch and streaming pipelines from operational and external sources
- Create Spark jobs, Kafka integrations and analytical data models
- Improve data quality, lineage, observability and pipeline reliability
- Prepare curated datasets for dashboards, forecasting and machine learning
When expertise matters
Companies usually bring in freelance specialists when data volume is rising, pipelines are unreliable or teams need to modernise a warehouse without interrupting operations. They may also need focused help migrating from legacy Hadoop environments, connecting cloud services or establishing governance. In Munich, remote collaboration can work well when documentation and ownership are clear; some programmes still benefit from on-site workshops and German-language communication.
Skills that set experts apart
Strong professionals understand more than individual tools. They can choose between batch and streaming designs, manage schema changes, tune distributed workloads and explain trade-offs in storage, latency, cost and accuracy. They also connect ingestion with security, metadata, data contracts, CI/CD and the needs of analysts or machine learning teams.
What good delivery looks like
Good Big Data work produces systems that remain understandable and dependable after handover. Look for practical evidence of monitored pipelines, repeatable deployments, tested transformations, controlled permissions and clear runbooks. A capable specialist asks about source quality, failure recovery, retention and business decisions before selecting a framework. They measure success through trusted outputs, not technology choice alone.
Frequently asked questions
Curious about Big Data? Here are the answers that come up again and again.
Big Data is used to process high-volume, fast-changing or highly varied information for reporting, forecasting, personalisation, fraud detection and operational decisions. It can support customer analytics, connected products, logistics, finance and industrial monitoring.
Big Data platforms are designed for broader data types and distributed processing, while a traditional warehouse often focuses on structured, curated reporting data. The right choice depends on workload, latency, governance, existing systems and the value of keeping raw information.
A strong Big Data specialist often combines SQL, Python, cloud storage, distributed computing and data modelling. Experience with Kafka, Spark, Airflow, Kubernetes, security, observability and machine learning pipelines can also be important.
The required depth depends on the assignment. Big Data migration, streaming and platform design usually call for a specialist who has handled production failures, data quality issues and operational ownership, while a defined pipeline extension may need a narrower skill set.
Yes, Big Data work is often suitable for remote collaboration because repositories, cloud environments and monitoring tools can be shared securely. On-site sessions may still help with architecture workshops, stakeholder alignment or access to systems that cannot be exposed remotely.
Before hiring a Big Data specialist, define source systems, expected freshness, data volumes, security requirements and the people who will operate the result. Clarify whether the assignment covers architecture, implementation, documentation, handover or ongoing support.
Quality Big Data delivery is observable, testable and maintainable. Ask how the specialist handles late or duplicate events, schema changes, failed jobs, access control, lineage, cost monitoring and recovery, then review examples of documentation and production ownership.
Hadoop remains part of many established data estates and its ideas still influence distributed storage and processing. Newer platforms may use cloud object storage, Spark, Flink, Trino or lakehouse patterns, so the best choice depends on the existing environment and migration goals.
The average hourly rate of freelancers in Munich, Germany who have used Big Data in their recent projects is 105 €, which corresponds to a daily rate of about 837 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Big Data in their recent projects, 94% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 19% hold a doctorate.
On average, freelancers in Munich, Germany who have used Big Data in their recent projects have 19 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 Big Data in their recent projects are German (97%), English (97%), and Spanish (21%).
The most common industries among freelancers in Munich, Germany who have used Big Data in their recent projects are Information Technology (85%), Professional Services (68%), and Banking and Finance (53%).
The most common business areas among freelancers in Munich, Germany who have used Big Data in their recent projects are Information Technology (94%), Product Development (82%), and Business Intelligence (79%).
Main locations of FRATCH Experts, who have recently used Big Data
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 
Cologne 
Frankfurt 
Stuttgart Request a free demo
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FRATCH CEO
