
Big Data Experts in Germany
matched in minutes from over 15,000 CVs with the power of AIHire experts who design data lakes, build streaming pipelines and turn large, varied datasets into reliable analytics. FRATCH connects you with vetted, available freelancers through fast and precise AI matching.
Meet FRATCH Experts in Germany, who have recently used Big Data
Dany-Armand D.
Last position:
Senior Data Scientist at ibg NDT GmbH
- Investigate the relationship between Eddy Current Testing (ECT) signals and microstructural properties
- Detect latent patterns in ECT data that reflect intrinsic material characteristics
- Develop and validate predictive models for microstructural classification and quantification, using hardness and case depth as benchmarks
- Apply Bayesian Structural Equation Modeling for advanced data analysis
Umut G.
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Hachem S.
Last position:
Machine Learning & BI Lecturer at EU Business School
- Taught ML, BI, and Big Data to Master's students.
Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM
Alexander H.
Last position:
Senior Product & Strategy Consultant at hegehofer.consulting
Design, development, and market launch of digital products and platforms – from strategic alignment and agile implementation to Go-to-Market and Go-Live, integrating AI into processes and products
Stefan O.
Last position:
Founder at ProtocolEngine.io
Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.
- Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
- Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
- Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
- Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
- Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
- Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.
Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.
Kiriakos K.
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
Maturing their API practices on both a business and technology level. My role covers strategy, architecture, developer advocacy as well as hands-on software engineering, enabling both technical teams and business leadership to adopt and act on API-centric principles effectively. Coincidentally, we also establish GitOps, DX and platform best practices with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, React, Node.js, TypeScript, Redocly, reactive programming, CDC, Golang, Gin, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Jens H.
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilization of an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Olga L.
Last position:
Business Analyst at VisualVest (Union Investment)
- Analyzed, structured, and documented business requirements for digital investment solutions, such as robo-advisors.
- Designed applications for new retirement products, including user flows, UX requirements, and functional specifications.
- Modeled and optimized business processes and coordinated with stakeholders while taking regulatory requirements in the financial sector into account.
Will O.
Last position:
Solution Architect at Polizei Behörde Stuttgart
Designed a migration strategy for WLS applications to BKA Cloud and Stack IT
Created a hybrid cloud for internal testing and development with Kubernetes
Transformed the IT landscape from an outdated monolithic architecture to a cloud-based architecture
Integrated new CI/CD processes using Azure Pipelines
Quadrupled the processing throughput for personnel security checks
Migrated personnel security screening applications to Docker-based applications
Implemented CI/deployment pipelines using Azure DevOps
Environment: Java Springboot, Kubernetes, Oracle Weblogic, OpenID, Camunda, JUnit, TOGAF
Prasad T.
Last position:
Solution Architect / Senior Manager – DTC E-Commerce Platform at BRITA
- Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
- Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
- Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
- Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
- Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
- Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
- Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka
Jan E.
Last position:
Participant in Project Management Certifications at Business Trends Academy BTA GmbH
Certifications earned:
- EXIN Agile Scrum Master
- EXIN Agile Product Owner
- GPM Basiszertifikat im Projektmanagement
- IPMA Level D
Aurelia H.
Last position:
Software Full Stack Developer at INNIO Jenbacher GmbH & Co OG
- Implementing and extending an Electron app based on TypeScript, React and Node.js to display stream content and technical data
- Extending a Kotlin backend for message processing via Kafka
- Extending various React modules
- Programming custom solutions for customers, including testing
- Creating documentation
- Development in accordance with Scrum processes
Used skills: React, React Hooks, Jest, Vitest, Typescript, Electron, IntelliJ, Vite, Github, Jira, Node.js, yarn, npm, pnpm, Swagger, OpenAPI, Storybook, Docker, Prettier, Eslint, tailwindcss, i18n, GraphQL, CoPilot, Postgres, JSON, Sqlite, trpc, influxdb, Java, Spring, Kotlin, Kafka, Git, Sonarcube
Torsten F.
Last position:
Data Analyst, Requirements Manager at Isabellenhütte Heusler GmbH
Analysis of the existing reporting platform, including processes and governance topics, with stakeholders from Sales and Marketing.
Detailed analysis and evaluation of customer-defined requirements for existing reporting and new dashboards to be established.
Support for stakeholders in managing sales processes and identifying KPI trends at an early stage.
Use of Microsoft Power BI as the central analysis and reporting platform.
Development of a proposal for the required further development of processes and the Power BI platform.
Documentation of AS-IS business processes and derivation of company-wide KPIs, including coordination with stakeholders.
Analysis and assessment of the customer's Power BI platform.
Analysis of processes and data governance.
Documentation of AS-IS business processes.
Development of recommendations for further developing processes and the reporting platform.
Design and implementation of dashboards in Power BI.
Development of company-wide KPIs and coordination with stakeholders.
Microsoft Power BI.
Data analytics.
KPI definition and reporting.
Dashboard design and data visualization.
Stakeholder management and requirements management.
Shanna T.
Last position:
Freelance Data Scientist & AI Developer at tellaev.de
- Portfolio development & customer acquisition
- Portfolio development (RAG, NLP fine-tuning, process automation with n8n) and active customer acquisition
- Positioning: GDPR-compliant, locally hosted AI solutions for SMEs
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
3 years

Positions per freelancer
12

Top business areas
Information Technology, Business Intelligence, Product Development

Top industries
Information Technology, Professional Services, Banking and Finance

Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
93%
Master's degree or higher
65%
Doctorate
16%

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
98%
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 Germany 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.
Discover detailed Big Data rate benchmarks:
Explore rate insightsAverage rates of experts in Germany 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 29 Oct 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 (84%)
- Professional Services (48%)
- Banking and Finance (45%)
- Manufacturing (43%)
- Automotive (37%)
- Education (35%)
- Healthcare (33%)
- Retail (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Big Data means
Big Data covers the methods and systems used to collect, store, process and analyze datasets that are too large, fast or varied for conventional databases. It supports batch processing, real-time analytics, machine learning preparation and operational reporting. The focus is not only volume, but also data quality, speed, lineage and business value.
What it builds
Companies use Big Data to create data platforms that bring together transactions, application events, sensor readings, documents and external sources. Typical deliverables include:
- Scalable data lakes and lakehouse environments
- Batch and real-time ingestion pipelines
- Event-driven analytics and monitoring
- Recommendation, forecasting and risk models
- Governed reporting and self-service data products
Ecosystem and tooling
The ecosystem commonly includes Apache Hadoop, Apache Spark, Apache Kafka, Apache Flink and Trino, alongside cloud storage and managed services. Specialists may work with Python, Java or Scala, SQL, distributed file formats such as Parquet, and orchestration tools including Apache Airflow. Strong security, metadata management and observability are essential across the stack.
When companies need specialists
Freelance expertise is useful when an existing platform cannot keep pace with data growth, when a migration has stalled or when teams need a reliable route from raw events to trusted insight. Common signals include:
- Slow or fragile ingestion and processing jobs
- Separate systems that cannot share consistent data
- Rising cloud or storage costs without clear ownership
- Delayed reporting for operational decisions
- New governance, retention or access requirements
Working in Germany
In Germany, Big Data supports manufacturing, mobility, energy, finance, retail, healthcare and public services. Projects often combine cloud environments with established on-premises systems, so professionals must handle hybrid architectures, strict access controls and clear documentation. Remote collaboration can work well when interfaces, ownership and delivery standards are agreed early; on-site workshops may help with complex legacy environments.
What strong professionals deliver
A strong specialist starts with the business question and defines useful data products before selecting tools. They design for failure, replay, schema changes, privacy and measurable operating costs rather than treating scale as the only goal. Look for evidence of production pipelines, clear testing practices, monitoring, incident handling and communication with both technical and non-technical stakeholders.
Frequently asked questions
Curious about Big Data? Here are the answers that come up again and again.
Big Data is used to process large, fast-moving or diverse datasets for analytics, forecasting, automation and operational decisions. A specialist may build ingestion pipelines, data lakes, streaming applications, recommendation systems or governed reporting layers.
Big Data systems distribute storage and processing across multiple resources and are designed for broad data volumes and formats. A traditional relational database remains a strong choice for structured transactions, while Big Data is often added for large-scale analytics, event processing or machine learning workloads.
Big Data work usually benefits from strong SQL, Python or Java, cloud storage, distributed computing and data modelling skills. Experience with Kafka, Spark, Airflow, Kubernetes, security, observability and machine learning pipelines can also be valuable, depending on the project.
Big Data projects need a professional who has handled production data flows similar to the proposed workload, not just completed tutorials. The right level depends on the scope, but architecture decisions, failure recovery, governance and cost control should be assessed before work begins.
Big Data work is often suitable for remote collaboration because pipelines, infrastructure and documentation can be managed through shared repositories and cloud environments. Germany-based projects may still require on-site sessions for access reviews, legacy system discovery or coordination with plant and operations teams.
Apache Spark is a strong option for large-scale batch processing, SQL analytics and unified data workloads. Apache Flink may fit continuous, low-latency stream processing better, while simpler SQL or managed services can be more appropriate when the data volume and transformation logic are modest.
Big Data quality is shown through production outcomes and sound technical reasoning, not by tool names alone. Ask how the professional handled schema changes, bad records, retries, monitoring, access control, testing and cloud cost management, then review relevant deliverables and references.
Big Data freelancers should clarify data sources, expected freshness, retention, ownership, security constraints and delivery milestones before committing. They should also understand the existing stack, such as Hadoop, Kafka or Spark, and confirm whether collaboration is remote, hybrid or tied to a German site.
The average hourly rate of freelancers in Germany who have used Big Data in their recent projects is 104 €, which corresponds to a daily rate of about 829 € based on an 8-hour working day.
Of the freelancers in Germany who have used Big Data in their recent projects, 93% hold at least a Bachelor's degree, 65% hold at least a Master's degree, and 16% hold a doctorate.
On average, freelancers in Germany who have used Big Data in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Germany who have used Big Data in their recent projects are German (98%), English (98%), and French (22%).
The most common industries among freelancers in Germany who have used Big Data in their recent projects are Information Technology (84%), Professional Services (48%), and Banking and Finance (45%).
The most common business areas among freelancers in Germany who have used Big Data in their recent projects are Information Technology (95%), Business Intelligence (74%), and Product Development (73%).
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.
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!

Berlin
Hamburg
Munich
Cologne
Frankfurt
Stuttgart