Big Data Experts in Berlin
matched in minutes from over 15,000 CVsHire experts who design scalable data platforms, build Apache Spark and Hadoop pipelines, and turn streaming and batch data into reliable analytics. Get fast, precise matching with vetted, available freelancers for your Big Data project.
Meet FRATCH Experts in Berlin, who have recently used Big Data
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.
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.
Peter M.
Last position:
Managing Partner without operational responsibilities at pt plus GmbH & Co. KG
- Full-service marketing agency for global technology groups
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.
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
Jan K.
Last position:
Data Expert at Manufacturing
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
Jonathan S.
Last position:
AI-Powered Product & Business Development at Self-Employed
- Developed websites, CRMs, and micro-SaaS using Lovable, Claude Code/ VS Studio (Vercel, Next.js, React, Supabase)
- Developed an analytics service to unlock automation gains
Ludvig G.
Last position:
Founder at Insightl.ai Lernplattform
- Attempted founding of a platform for career development and personal coaching
- Top 3 placement in the Berlin-Brandenburg business plan competition
- Conducted independent market analysis and user research
- Built a comprehensive knowledge graph for roles, skills, and experiences
- Data transformation and setting up data pipelines on Azure
André G.
Last position:
IT Consulting Project Management / Engineering Subproject Management at T-Systems (on assignment for government agencies)
- Projects for federal networks (NdB).
- CR management, EoL change requests, design and documentation according to ITSCM.
- Data center planning.
- Project management and engineering subproject management.
- Software development for virtual server environments according to BSI.
Julien L.
Last position:
MLOps Engineer at SAMGEN
- Building and scaling cloud infrastructure on GCP to support a SaaS platform for industrial clients
- Designing and implementing a data-driven DevOps pipeline for streamlined deployment and CI/CD workflows
- Collaborating with Data Science team on MLOps workflow to automate integrated retraining
Konstantin S.
Last position:
Head of Cyber Defense Unit at Simonow Consulting GmbH
- Established the Cyber Defense Unit following a major cybersecurity incident
- Recruited a team of Cybersecurity Architects, Engineers and Senior Security Analysts
- Managed the team’s resources and activities in defining and implementing a target cybersecurity architecture, monitoring the IT landscape, detecting and responding to security events and incidents, and consulting other IT stakeholders in their efforts to improve the organization’s cybersecurity posture (comparable to Technical CISO role)
- Led the separation of Information Security (governance, risk, compliance) and Cyberdefense Unit (technical cybersecurity), in close collaboration with the CISO
- Led the selection and onboarding of external Security Operations Center (MSSP)
Nick P.
Last position:
Global ERP, AI & Supply Chain Project Manager at Dr. Martens
Led the end-to-end delivery of a SAP Supply Chain Management (SCM / TD / SD) ERP programme, covering project initiation, detailed requirements gathering, operating model definition, system design, build, testing, cutover, and global Go Live across Europe, Asia, and North America. Ensured the ERP solution supported key supply chain, manufacturing, and planning operations to enable future business growth.
Conducted cross-functional workshops with Supply Chain, Procurement, Planning, Manufacturing, and Logistics teams to capture business requirements, define the future operating model, and map end-to-end system design. Consolidated over 150 requirements into structured documentation aligned with SAP standards.
Shaped solution design and vendor engagement during the early discovery phase, supporting selection of best-fit technology partners and ensuring the system design covered production planning, inventory management, warehousing, logistics, and supply chain forecasting.
Managed D365 configuration and troubleshooting, ensuring alignment with business processes and resolving integration issues between D365, SAP SCM modules, and surrounding systems.
Supported Grain data model changes to lead ingestion of planning data into Snowflake and Footprint, enabling enterprise reporting and analytics development.
Managed scope, timelines, risks, and dependencies across international teams spanning Europe, Asia, and the US, maintaining integrated project plans, issue logs, and executive reporting to drive stakeholder alignment and delivery momentum.
Enabled the integration of AI-powered demand forecasting tools into supply chain planning processes, improving forecast accuracy, inventory turnover, and operational decision-making across multiple regions.
Led SIT, UAT, and data migration phases, including design of test scenarios, defect triage management, and coordination of test execution to validate supply chain and manufacturing workflows prior to deployment.
Delivered detailed cutover planning, business readiness activities, and hypercare support, ensuring a smooth and coordinated Go Live and full operational handover to business teams.
Andrej B.
Last position:
Lead UX Design Engineer at Journexx GmbH
- Leading, designing, and developing the UX and UI strategy and implementing it for the platform
- Creating style guides and design systems in Figma
- Creating a generic end-to-end layout structure for big data cockpits in Figma and Sass (CSS, design tokens)
- Workflows, wireframes, user research, and rapid prototyping
- Preparing and facilitating workshops and discoveries
- Integrating designs and layouts into existing frontend templates
- Prototyping (low-/mid-/high-fidelity) of various apps for journalists and publishers
- Developing showcases for iOS and Android, design thinking, qualitative and quantitative user testing, and A/B testing
- Frontend development in close collaboration with design teams
- Active change management in the publishing and journalism sector and with stakeholders
- Company-wide communication and info hub for teams
- Raising awareness and getting buy-in for digitalization and new products
- Creating concepts and designs for gamification elements on the platform
- Convincing major industry players (e.g., WAN-IFRA) about new concepts and revenue streams
- Developing new cloud-native apps and revenue strategies
- Preparing and creating various materials for change processes
- Creating presentations, mini-apps, and info materials to support change campaigns
- Leading a total of three teams
Discover over 15,000 top freelancers
Statistics of experts using Big Data
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 19 years)
Position duration
2.3 years (Germany: 3 years)
Positions per freelancer
11 (Germany: 12)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Media and Entertainment
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
91% (Germany: 93%)
Master's degree or higher
41% (Germany: 65%)
Doctorate
5% (Germany: 16%)
Certifications per freelancer
3
Most common languages
German, English, Spanish
Speak two or more languages
92% (Germany: 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 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 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 (88%)
- Banking and Finance (48%)
- Media and Entertainment (44%)
- Professional Services (40%)
- Retail (40%)
- Education (36%)
- Manufacturing (32%)
- Automotive (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Data at scale
Big Data covers the methods and systems used to collect, store, process and analyse datasets that exceed the practical limits of conventional databases. It supports structured, semi-structured and unstructured information, from clickstreams and sensor events to transactions, documents and media. The work combines distributed computing, data architecture and analytical delivery.
Platforms and tools
The ecosystem includes Apache Hadoop for distributed storage and processing, Apache Spark for batch and streaming workloads, and Kafka for event transport. Specialists also work with cloud storage, data warehouses, lakehouses, SQL, Python, Scala and Java. Orchestration, catalogues, lineage, access controls and observability keep pipelines usable in production.
What companies build
- Batch pipelines that consolidate operational and external data
- Streaming systems for alerts, recommendations and real-time decisions
- Lakehouses and analytical warehouses for reporting and exploration
- Feature pipelines that prepare data for machine learning
- Governance workflows for quality, lineage and controlled access
These systems appear in retail, finance, logistics, media, manufacturing, research and public services. In Berlin, companies often need data foundations that connect product, operations and analytics teams across remote or on-site work.
When expertise matters
Companies bring in freelance specialists when data volume, velocity or variety exposes limits in existing systems. Typical triggers include a migration from legacy databases, unreliable pipelines, rising cloud costs or a move from batch processing to streaming. Experts can assess the current architecture, define a practical target state and deliver the first production workloads.
Delivery skills
Strong professionals clarify data ownership, retention, access and service-level needs before selecting tools. They design for partitioning, schema evolution, retries, backfills and failure recovery, then automate testing and deployment. They also document decisions and explain trade-offs clearly to product, security and analytics stakeholders.
Choosing a specialist
Look for evidence of production systems rather than familiarity with tool names alone. A capable Big Data specialist can trace data from source to dashboard, explain bottlenecks with measurable evidence and show how quality is monitored. For Berlin-based collaboration, agree early on working hours, language, workshop expectations and the split between remote delivery and on-site sessions.
Frequently asked questions
Curious about Big Data? Here are the answers that come up again and again.
Big Data is used to collect and process large, fast-changing or varied datasets for reporting, forecasting, recommendations, fraud detection and operational decisions. It is also the foundation for many machine learning and real-time analytics systems.
Big Data approaches are designed for distributed storage and processing across varied data types and workloads. A traditional warehouse is usually more structured and focused on governed analytical queries, although modern lakehouses combine elements of both approaches.
A strong Big Data specialist may work with Apache Spark, Hadoop, Kafka, cloud object storage, SQL and orchestration tools. The right combination depends on whether the project needs batch processing, event streaming, a lakehouse, machine learning preparation or governed reporting.
Big Data work benefits from expertise in data modelling, distributed systems, cloud infrastructure, DevOps, security and machine learning operations. Knowledge of Python, Scala or Java is useful, but sound decisions about schemas, reliability and ownership matter just as much.
The required Big Data experience depends on the system’s risk, scale and operational maturity rather than on a fixed career level. A small pipeline may need focused delivery skills, while a regulated platform or high-volume streaming system calls for proven architecture, governance and incident experience.
Big Data projects are often well suited to remote collaboration because code, infrastructure and documentation are shared digitally. Berlin teams should still define communication windows, workshop routines, access procedures and any occasions when on-site discovery or stakeholder sessions add value.
Ask a Big Data specialist to explain a production pipeline from ingestion through storage, processing, quality checks and consumption. Look for clear handling of failures, schema changes, security, cost and observability, supported by concrete deliverables rather than a list of tools.
Big Data is justified when data volume, speed, variety or analytical complexity creates a genuine limitation for simpler database or warehouse designs. A good specialist should also be willing to recommend a simpler architecture when it meets the requirements with less operational overhead.
The average hourly rate of freelancers in Berlin, 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 Berlin, Germany who have used Big Data in their recent projects, 91% hold at least a Bachelor's degree, 41% hold at least a Master's degree, and 5% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Big Data in their recent projects have 17 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 Big Data in their recent projects are German (96%), English (96%), and Spanish (20%).
The most common industries among freelancers in Berlin, Germany who have used Big Data in their recent projects are Information Technology (88%), Banking and Finance (48%), and Media and Entertainment (44%).
The most common business areas among freelancers in Berlin, Germany who have used Big Data in their recent projects are Information Technology (100%), Business Intelligence (68%), and Product Development (68%).
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.
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