Big Data Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Big Data
Jens Henneberg
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilizing 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
Sandra Klinkenberg
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 Hermann
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.
Umut Gülac
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.
Patrick Hohensee
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.
Gerhard Kolar
Last position:
Senior Project Manager and Construction Manager at HENSOLDT Optronics GmbH
- Building the data center in Oberkochen (defense area)
- Planning the fiber optic ring, simulation of Wi-Fi coverage
- Cable routing 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 network infrastructure and server technologies in the SAP environment
- Pré-sales support and setting up change management
- Independent coordination of utilities according to time, budget and quality
- Mapping the project in MS Project and SERVICENow
- Development and design of hardware and software
- Demand management and portfolio management
- Building a risk register and migration plan
- Preparation of payment-supporting documents in coordination with the responsible finance and commercial functions
- Budget: 5 Mio. - 34 FTE
Halil Oeztoprak
Last position:
Senior Cloud Operations & DevSecOps Engineer (Azure / Terraform / CI-CD) at KfW Bankengruppe
Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).
Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.
Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.
Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.
Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.
Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.
Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.
CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.
Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.
Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.
OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.
Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).
Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.
Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.
Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.
SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.
Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.
Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.
CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.
Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.
Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.
Kiriakos Krastillis
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
maturing their API Practices on both, a Business and Technology level. My role encompasses 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, nodejs, typescript, redocly, reactive programming, CDC, golang, gingonic, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Alexander Zhirov
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 Grunert
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 Lukin
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
Thomas Meyer
Last position:
Executive Consultant, Coach to Management at International consulting firm
- Support to management on critical strategic topics with high investment volumes (e.g. large project > EUR 250 million).
- Support for the financing of large projects with a credit volume of EUR 100 million.
- Advice on difficult personnel issues and on filling leadership positions.
- Leadership and management in virtual project environments.
- Strategic consulting on digitalization as well as financing and equity topics.
- Impulse giver and advisor for stuck negotiations, contract design, and solution options.
Alexander Bromberg
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
Julian Hillebrand
Last position:
IT Project Manager AI product for automating knowledge-intensive processes at Leading provider of large-scale catering & food services
Project: Concept and implementation of an AI product for four business use cases
Project management of 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 from CRM and document data, voice-based capture and structuring of reports, detection and merging of duplicates in master data, and data-based market analysis. A central focus was a privacy-compliant architecture that passed the internal IT security review and enabled productive use.
- Translating business requirements into clearly defined AI use cases with a clear product scope and clear value proposition
- Selecting and evaluating models and architecture options for text extraction, speech-to-text and context enrichment from business systems, including LLM integration, function calling and retrieval
- Designing and enforcing an architecture with European hosting, data minimization and masking of personal data as a prerequisite for approval
- Managing the interfaces between business, IT, IT security and the external development partner under restrictive data access conditions
- Coordinating with CIO and executive management on data access, risk assessment and approval decisions
- Preparing the transition into productive use
Prasad Tilloo
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
91%
Master's degree or higher
64%
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 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany 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 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it covers
Big Data is the work of collecting, moving, storing, and processing very large datasets across distributed systems. It is used for analytics, reporting, search, fraud checks, log analysis, and operational data products. Common stacks include Hadoop, Spark, Kafka, Hive, and cloud data services.
Typical work
- Build batch pipelines for large source systems
- Set up streaming flows for near real-time events
- Design data lakes, warehouses, and lakehouse layers
- Optimize jobs, storage formats, and query paths
- Add monitoring, lineage, and data quality checks
Where it fits
Companies bring in Big Data specialists when data volumes outgrow manual handling or simple database setups. In Germany, that often means industrial data, mobility, finance, retail, media, or logistics workloads. The work can be remote or on-site, but close collaboration helps when teams need access to sensitive data or legacy systems.
Ecosystem skills
Strong professionals know more than one tool. They understand Spark, Hadoop, Kafka, SQL, Python, and cloud services such as AWS, Azure, or Google Cloud. They also know how to choose file formats, partitioning, orchestration, and access controls that keep systems stable and usable.
What good specialists deliver
Good Big Data experts write clear pipeline code, keep costs under control, and make data trustworthy. They can read existing jobs, fix bottlenecks, and explain trade-offs in plain language. They also work well with analytics, security, and business teams, which matters when data products have many users.
When to hire
If your pipelines fail, your queries are slow, or teams disagree on where data lives, you need focused help. Freelance specialists are useful for migrations, platform rebuilds, performance tuning, and short project bursts. They are also valuable when your internal team needs a second set of hands for a critical delivery.
Frequently asked questions
Curious about Big Data? Here are the answers that come up again and again.
Big Data is used to handle large, fast, or varied datasets that regular systems struggle to process well. Companies use it for reporting, event analysis, customer behavior tracking, fraud detection, search, and operational dashboards. It usually sits behind pipelines, data lakes, or analytics platforms.
Big Data work often focuses on distributed processing, streaming, and raw or semi-structured data at scale. A data warehouse setup is usually more structured and query-focused. In many companies, the two overlap: Big Data systems feed the warehouse, and the warehouse supports business reporting.
Big Data projects still use Hadoop in some environments, especially where older clusters or HDFS-based setups remain in place. Spark is now common for faster batch and in-memory processing, but it does not replace every Hadoop component. Many real systems combine Spark with Kafka, Hive, and cloud storage.
A strong Big Data specialist usually knows SQL, Python, and at least one orchestration tool such as Airflow. Knowledge of Kafka, Spark, Hadoop, cloud platforms, and data modeling is also valuable. For production work, data quality, security, and monitoring matter just as much as code.
A Big Data project needs the right depth, not just general data experience. Small proof-of-concepts may only need a specialist who can wire systems together cleanly, while migrations, performance tuning, or governed pipelines need deeper platform knowledge. The more data sources and teams involved, the more important proven delivery becomes.
Yes, Big Data work is often well suited to remote delivery because much of the work happens in code, notebooks, and infrastructure configuration. In Germany, on-site collaboration can still help when the project involves restricted systems, workshops, or close work with business teams. Many engagements use a hybrid setup.
Look for someone who can explain design choices, not only name tools. A strong Big Data professional has shipped real pipelines, handled failures, tuned performance, and dealt with data quality issues. Ask for examples of migration work, production incidents, or systems they improved end to end.
Big Data is the scale and system side of the problem: storing and processing large datasets across distributed tools. Data engineering is broader and includes pipelines, modeling, integration, and delivery practices around data. In practice, many specialists work across both, especially in analytics-heavy teams.
The average hourly rate of freelancers in Germany who have used Big Data in their recent projects is 105 €, which corresponds to a daily rate of about 843 € based on an 8-hour working day.
Of the freelancers in Germany who have used Big Data in their recent projects, 91% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 17% 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 (99%), English (97%), and French (21%).
The most common industries among freelancers in Germany who have used Big Data in their recent projects are Information Technology (83%), Professional Services (47%), 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 (94%), Business Intelligence (75%), and Product Development (74%).
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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