Big Data Experts
to turn complex data into scalable products, matched in minutes with AIHire experts who design data lakes, build Apache Spark pipelines and operate Hadoop-based processing environments. FRATCH connects you with vetted, available freelancers whose Big Data experience matches your technical scope quickly and precisely.
Meet FRATCH Experts who have recently used Big Data
Gerhard K.
Last position:
Senior Project Manager and Site Manager at HENSOLDT Optronics GmbH
- Set-up of the data center in Oberkochen (Defence division)
- Planning of the fiber-optic ring and simulation of Wi-Fi coverage
- Installation plan for WAN and LAN cables for office and production (infrastructure)
- Adaptation of the SAP system (R3) for the Oberkochen site (software)
- IT transformation of the SAP system to SAP HANA
- Planning of network infrastructure and server technologies in the SAP environment
- Pre-sales support and establishment of change management
- Independent coordination of utilities according to time, budget and quality
- Mapping of the project in MS Project and SERVICENow
- Development and design of hardware and software
- Demand management and portfolio management
- Set-up of a risk register and migration plan
- Preparation of payment-supporting documents in coordination with the responsible finance and commercial functions
- Budget: 5 million - 34 FTE
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
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.
Sandra K.
Last position:
Webinar Leader - Blackout Prevention and Preparation at SANDRA KLINKENBERG • Management Consultant, self-employed independent business consultant
- Webinar on Blackout - Brownout - Power failure - how do I recognise it and what can I do?
Martin H.
Last position:
Lead Product Owner at Energy
- Team leadership: Prioritization and coordination of four cross-functional teams.
- Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
- Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
- Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
- Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
- Organizational development: Improving communication and decision-making structures across all organizational levels.
- Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
- Quality assurance: Ensuring high quality standards in processes, services, and deliverables.
Patrick H.
Last position:
Lead Technical Recruiter | Business Partner AWS EMEA at Amazon Web Services (AWS)
- Partnered with senior stakeholders across AWS EMEA to drive talent strategy, partner development, and business growth in the cloud ecosystem.
- Focus areas:
- Collaboration with Sales & Partner Management on Go-to-Market initiatives
- Advisory on long-term resource strategy for Cloud, Data, and Security Divisions
- Supporting internal innovation teams in scaling AI and automation projects
- Result: Contributed to AWS’s expansion in Central Europe by aligning business, technology, and people strategy.
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
Julian H.
Last position:
IT Project Manager AI Product for Automating Knowledge-Intensive Processes at Leading provider of large-scale catering & food services
Project: Design and implementation of an AI product for four business use cases
Project management for an AI project at a leading provider of large-scale catering and food services, where a production-ready AI product for four use cases was implemented together with an external development partner: automated briefings based on CRM and document data, voice-based capture and structuring of reports, detection and consolidation of duplicates in master data, and data-based market analyses. A key focus was a data-protection-compliant architecture that passed the internal IT security review and enabled production use.
- Translation of business requirements into clearly defined AI use cases with a focused product scope and clear value proposition
- Selection and evaluation of models and architecture options for text extraction, speech-to-text, and context enrichment from business systems, including LLM integration, function calling, and retrieval
- Development and implementation of an architecture with European hosting, data minimization, and masking of personal data as a prerequisite for approval
- Management of interfaces between business departments, IT, IT security, and the external development partner under restrictive data access conditions
- Coordination with the CIO and executive management levels on data access, risk assessment, and approval decisions
- Preparation for the transition to production use
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.
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
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
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
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
92%
Master's degree or higher
65%
Doctorate
17%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
98%
Based on our profile pool as of 26 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 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 26 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 (83%)
- Professional Services (47%)
- Banking and Finance (46%)
- Manufacturing (43%)
- Automotive (36%)
- Education (34%)
- Healthcare (33%)
- Retail (32%)
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 and processing data that is too large, fast or varied for conventional databases. Teams use it to transform event streams, application logs, customer records, sensor readings and documents into reliable datasets for analytics, reporting and machine learning.
Where it is used
Big Data supports products and operations that depend on continuous, high-volume information.
- Customer behavior analysis and recommendation systems
- Fraud detection and risk monitoring
- IoT, manufacturing and logistics telemetry
- Personalization, search and advertising analytics
- Real-time dashboards and regulatory reporting
Core ecosystem
Strong specialists understand how storage, processing, orchestration and governance fit together. Common tools include Hadoop Distributed File System, Apache Spark, Apache Kafka, Apache Flink, Hive, Trino and cloud services such as Amazon EMR, Google BigQuery and Azure Databricks. They also work with Python, Scala, SQL, Docker and Kubernetes where the delivery model requires it.
Typical project work
Freelance professionals design lakehouse and data lake architectures, define batch and streaming pipelines, and migrate workloads from legacy warehouses. Their deliverables can include ingestion frameworks, Spark jobs, Kafka topics, data quality checks, metadata models, access controls and monitoring. They also document operating procedures so internal teams can maintain the environment.
When expertise matters
Companies bring in Big Data specialists when data volumes grow faster than existing systems, analytics arrive too late or separate teams produce conflicting figures. Outside expertise is useful during cloud migrations, platform modernizations, real-time use cases and acquisitions that combine different data sources. A focused professional can assess the current architecture, reduce processing bottlenecks and establish a practical delivery plan.
What strong professionals bring
Quality work goes beyond selecting a popular framework. Strong experts connect business questions to measurable data products, choose batch or streaming processing for a clear reason and design for failure, recovery and cost control. They understand schema evolution, partitioning, lineage, privacy, security and data quality, and they validate results with representative workloads. Clear communication matters when remote specialists collaborate with product, security and operations teams across locations.
Frequently asked questions
Need clarity? These are the questions we hear most often about Big Data.
Big Data is used to process large, fast-changing or varied datasets for analytics, automation and machine learning. Common applications include fraud detection, recommendations, operational monitoring, IoT analysis and near-real-time reporting.
Big Data architectures are built to handle broader data types and more variable processing demands than a traditional warehouse. A warehouse remains strong for governed, structured reporting, while Big Data tools such as Spark, Kafka and cloud lakehouses support large-scale batch or streaming workloads.
A strong Big Data specialist usually combines distributed processing with SQL, Python or Scala, cloud storage and orchestration. Knowledge of Kafka, Kubernetes, data modeling, security, observability and machine learning workflows can also be important, depending on the project.
The right level depends on the risk and scope of the work, not on a fixed number of years. Big Data projects involving production migrations, streaming reliability or governance need a professional who has handled comparable systems, while a contained pipeline or proof of concept may need a narrower specialist.
Yes, Big Data work is often suitable for remote collaboration because repositories, cloud environments and monitoring tools can be accessed securely online. On-site sessions may still help with discovery, regulated environments or close coordination with infrastructure and business teams.
Ask a Big Data professional to explain a comparable architecture, including ingestion, storage, processing, recovery and data quality controls. Review the clarity of their trade-offs and documentation, then use a practical discussion about latency, schema changes, security and failure handling rather than relying on tool names alone.
Hadoop remains relevant in some established environments, especially where HDFS and related ecosystem components support existing workloads. Newer projects often use cloud object storage, Spark, managed lakehouse services or streaming systems, so the best choice depends on the current estate, constraints and migration goals.
Before starting, a Big Data freelancer should clarify data sources, ownership, expected freshness, access rules, service-level needs and the target cloud or on-premises environment. They should also confirm how success will be measured, who operates the pipeline after delivery and whether collaboration requires shared working hours or on-site availability.
The average hourly rate of freelancers who have used Big Data in their recent projects is 104 €, which corresponds to a daily rate of about 835 € based on an 8-hour working day.
Of the freelancers who have used Big Data in their recent projects, 92% hold at least a Bachelor's degree, 65% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers 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 who have used Big Data in their recent projects are German (99%), English (98%), and French (20%).
The most common industries among freelancers who have used Big Data in their recent projects are Information Technology (83%), Professional Services (47%), and Banking and Finance (46%).
The most common business areas among freelancers who have used Big Data in their recent projects are Information Technology (95%), Business Intelligence (75%), and Product Development (73%).
Main locations of FRATCH Experts, who have recently used Big Data
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Vienna Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Zurich Geneva Basel Bern Countries:
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FRATCH CEO
