Big Data Experts in Stuttgart
to turn complex data into reliable decisions, matched in minutes with AIHire experts who design data platforms, build Spark and Hadoop pipelines, and deliver analytics-ready datasets for industrial, automotive and digital businesses. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts in Stuttgart, who have recently used Big Data
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Transformed the IT landscape from an outdated monolithic architecture to a cloud-based architecture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
Lothar H.
Last position:
Solution Manager for the investigation PoC and exchange and refinement of an existing cloud and IoT power plant control system at Shell AG and NEXT Kraftwerke GmbH
- Investigation PoC and exchange and refinement of an existing cloud and IoT power plant control solution for certificate management of renewable energy power plants (solar, wind, biomass and others) of the largest European renewable energy power plant operator in this field, including investigation of the IoT devices used in the field and their integration and network connection with the aim of automated PKI key management.
- Messaging with Kubernetes for large API-connected enterprise applications
- Risk and Attack Vector Analysis, Software Quality & Bug Assessments
- Agile Workload Scheduling via Jira & ConJluence
- Evaluation of message streams Pub/Sub for MQ and KaJka.
- Various tests with “best design approaches” regarding resilience patterns such as Circuit Breaker Designs, Throughput Measurement and Monitoring, Bulkhead Governors - for robust EA design
- Integration of API Management with IBMs API Connect to Kubernetes - for agnostic Microservices API Management Designs. Google Apigee
- Solution Health Check Approaches for Load Burst Situations + Remedy
- Research and investigation of available potential subcontractors in the coordinating role as Solution Manager. CIS20 Controls.
- Dread and Stride Security Assessments.
Albert F.
Last position:
Lead Product Owner at CMBlu Energy AG
- Lead Product Owner for 4 development teams
- Leading and coordinating a greenfield project with parallel implementation of core components by independent teams; managing dependencies and resources
- Establishing a data lakehouse approach, including analysis of data volumes and future requirements as part of a cloud migration (best-of-breed approach)
- Responsible for requirements analysis, selection, and piloting of a LIMS/ELN system, supported by advising decision-makers and managing external vendors
- Introducing and managing an OpenWeb UI and Azure OpenAI-based RAG system to support knowledge extraction and data-driven analyses
- Setting up, configuring, and managing Jira projects, as well as developing project-specific workflows and automations
- Implementing classic Scrum processes with all ceremonies and taking on the Scrum Master role for all involved teams
- Assisting in hiring through interviews and assessments from a product owner's perspective
- Making key architectural decisions, including selecting the platform for the data lakehouse (Databricks) and the strategic integration of LIMS and analytics platforms
Thomas A.
Last position:
Interim Management at Vincorion Power Systems GmbH
- Process and project management to optimize products and development processes for energy systems
- Technical risk management
- Requirements engineering and system architecture
- System FMEA of power generator units and energy storage modules aiming for generic structures
- Claims management according to Section 313 of the German Civil Code
- Regulatory environment: military and NATO standards, AQAP, VG norms
Dennis D.
Last position:
Founder at Latence
- Founded Latence to commercialise runtime safety patterns from HALO as a deployable product.
- Built end-to-end as single technical founder with open-source stack on NVIDIA ecosystem.
- Developed TRACE: real-time safety layer for knowledge agents and RAG pipelines with groundedness scoring, prompt-attack detection, GDPR redaction, context compression, audit-ready traces.
- Developed vLLM Factory: production inference framework on vLLM with custom Triton kernels and 12 parity-validated plugin models, achieving up to 11.7Ă— throughput vs vanilla PyTorch.
- Developed ColSearch: single-node multi-vector late-interaction retrieval engine with Rust SIMD and fused CUDA, achieving 3.12Ă— FastPlaid geomean QPS on BEIR-8 and a 1.58-bit quantized lane 6.4Ă— smaller than FP16.
- Developed llm-opt: LLM compression research framework with hierarchical importance, structured pruning, tabu search, knowledge distillation.
Dean R.
Last position:
CEO / Chief Scientist at ENUM
- Blockchain platform technology
- Blockchain digital platform / Digital Economy.
Harshal V.
Last position:
Project Intern at Global Shapers Stuttgart Hub
- Part of sustainability workshops and youth development sessions (“Purpose Factory”).
Tom D.
Last position:
Co-founder & CTO at Ferris Labs AG
- Focused on talent and product development as well as solution architecture
Joachim K.
Last position:
Incubator at DatenBerg GmbH
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
3.3 years (Germany: 3 years)
Positions per freelancer
14 (Germany: 12)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Automotive, Professional Services
Certification focus areas
Information Technology, Operations, Product Development
Bachelor's degree or higher
86% (Germany: 93%)
Master's degree or higher
86% (Germany: 65%)
Doctorate
14% (Germany: 16%)
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 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Stuttgart 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 Stuttgart 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 (89%)
- Automotive (78%)
- Professional Services (67%)
- Government and Administration (67%)
- Manufacturing (56%)
- Education (44%)
- Energy (44%)
- Transportation (44%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Big Data covers
Big Data refers to the methods and systems used to collect, store, process and analyse data at a scale, speed or variety that traditional databases cannot handle efficiently. It supports structured records, event streams, sensor readings, documents and other complex sources. The goal is useful, trustworthy information for operations, products and decisions.
Platforms and tooling
A Big Data solution often combines distributed storage, batch processing, stream processing and data management. Common technologies include Apache Hadoop, Apache Spark, Kafka, Hive, Flink, cloud data lakes and lakehouse architectures. Strong specialists also work with SQL, Python or Java, orchestration tools, container environments and observability systems.
What companies build
Big Data supports systems that need to process large or continuously changing datasets.
- Data lakes and lakehouse platforms for analytics and machine learning
- Real-time pipelines for telemetry, fraud detection and operational monitoring
- Customer, supply-chain and production data products
- Reporting layers, feature stores and self-service analytics environments
When freelance expertise helps
Companies often bring in freelance specialists when an existing data landscape has become difficult to scale, govern or maintain. They can assess architecture, connect fragmented sources, modernise Hadoop workloads, or establish reliable batch and streaming pipelines. In Stuttgart, this work can support automotive, manufacturing, logistics and research organisations, with on-site workshops combined with remote delivery when appropriate.
Skills behind reliable systems
Successful Big Data work requires more than choosing a processing engine. Professionals understand data modelling, partitioning, schema evolution, distributed computing, security, data quality and cost control. They also connect technical delivery with business requirements, define ownership and document how data moves from source to decision.
How to assess specialists
Look for evidence of production systems rather than tool lists alone. A strong specialist can explain trade-offs between batch and streaming, show how failures are handled, and describe measurable data-quality controls without exposing confidential information. Experience with cloud services, DevOps, governance and clear stakeholder communication is valuable, especially when teams collaborate across Stuttgart and remote locations.
Frequently asked questions
Key details about Big Data, drawn from the questions we get asked most.
Big Data is used to collect and analyse large, fast-moving or varied datasets. Companies apply it to connected products, predictive maintenance, recommendation systems, fraud detection, logistics planning, customer analytics and industrial operations.
Big Data environments are designed for distributed processing and may handle raw, semi-structured and streaming data. A traditional warehouse usually focuses on curated structured data and governed reporting, although modern lakehouse systems increasingly combine both approaches.
A strong Big Data specialist often combines Spark or Hadoop knowledge with SQL, Python or Java, Kafka, cloud storage and workflow orchestration. Data modelling, machine learning operations, DevOps, security and data governance can also be important, depending on the project.
The right level for Big Data depends on the system’s scale, risk and stage. A focused pipeline improvement may need a specialist for a defined delivery phase, while a platform migration or streaming architecture benefits from someone who has owned production systems and can guide technical decisions.
Big Data work is often suitable for remote collaboration because repositories, cloud environments and monitoring tools are accessible online. On-site workshops in Stuttgart can still help with source-system discovery, factory or operations context, stakeholder alignment and data ownership decisions.
Choosing between Apache Spark and Apache Hadoop depends on the workload and existing environment. Spark is widely used for fast batch and streaming computation, while Hadoop components may remain relevant for established storage and processing estates; a specialist should evaluate migration effort, skills and operating costs.
Good Big Data work has clear data contracts, repeatable pipelines, monitoring, controlled access and documented recovery procedures. Ask how the specialist handles late events, schema changes, duplicate records, failed jobs and data-quality incidents, not just which tools they have used.
A Big Data engagement may involve unclear source ownership, changing schemas and dependencies across analytics, software and operations teams. Freelancers should expect to clarify business outcomes, work with distributed systems, communicate trade-offs and leave behind documentation that internal teams can operate.
The average hourly rate of freelancers in Stuttgart, Germany who have used Big Data in their recent projects is 108 €, which corresponds to a daily rate of about 862 € based on an 8-hour working day.
Of the freelancers in Stuttgart, Germany who have used Big Data in their recent projects, 86% hold at least a Bachelor's degree, 86% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Stuttgart, Germany who have used Big Data in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 3.3 years.
The most common languages among freelancers in Stuttgart, Germany who have used Big Data in their recent projects are German (100%), English (100%), and Spanish (11%).
The most common industries among freelancers in Stuttgart, Germany who have used Big Data in their recent projects are Information Technology (89%), Automotive (78%), and Professional Services (67%).
The most common business areas among freelancers in Stuttgart, Germany who have used Big Data in their recent projects are Information Technology (100%), Product Development (89%), and Business Intelligence (78%).
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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Hamburg 
Munich 
Cologne 
Frankfurt Request a free demo
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Philipp Thomaschewski
FRATCH CEO
