Apache Hadoop Experts in Berlin
in minutes from over 15,000 CVs with the power of AI.Hire experts who can run HDFS and YARN environments, tune Spark on Hadoop, and build reliable batch data pipelines. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Apache Hadoop
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.
Joachim Groth
Last position:
Software Coordinator / Business Analyst / Developer at Kassenärztliche Vereinigung Sachsen
- Leading coordination between business units and IT
- Coordinating development and testing
- Business analysis and structured requirements gathering
- Specifying functional and technical requirements
- Integrating interfaces to internal systems
- Developing SQL queries and reports
- Documentation in Confluence Result: On-time go-live, structured and agreed project basis, ensuring a coordinated project workflow.
Nune Isabekyan
Last position:
Fractional CTO at OpsWorker
OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.
Raphael Mankopf
Last position:
Founder / Quant Developer at Market Maker
- Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
- Data and trade architecture development for liquidity provision
Nino Sandmeier
Last position:
Freelancer in Data Science at International Companies
Proceeding what was started in 10/2023, offering data science development skills fulltime to international clients
Helping companies learn more about their existing (unstructured) data, optimize processes and technical systems, and derive solutions for their problems
Tools and technology used: Python (sklearn, pandas, numpy, Django, sqlAlchemy, pyTorch), Matlab, Docker, AWS EC2, Lambda, S3, SQL, MySQL, Hadoop & Spark, Machine Learning, DNN, AI, Jira, Confluence, Git, CI/CD, GitLab, Jenkins
Rohini Adavappa
Last position:
Senior Product Manager at Zalando
- Product strategy & vision: Led campaign performance reporting platform serving 700+ partners, transformed manual MSTR-based weekly reporting to real-time self-service platform enabling partner autonomy and operational efficiency
- Strategic roadmap management: Led phased migration prioritizing Performance campaigns (70% revenue) ahead of Awareness and Engagement, driving iterative platform evolution aligned with objectives, partner feedback, GDPR compliance, and data retention policies
- User research & customer discovery: Conducted regular user interviews with partners to understand reporting needs, decision-making processes, and additional KPI requirements, translating insights into platform enhancements and feature prioritization
- Cross-functional leadership: Collaborated with Product Consultants, analysts, data engineers, frontend teams, and product marketing to execute seamless platform migration, reducing PC team size by 2 FTEs while improving service quality
- Scaled user adoption: Strategically onboarded partners starting with top 30 partner-program partners, expanding to all 700+ partner-program and wholesale partners through user education documentation, training coordination, and iterative feedback incorporation
- Data-driven product optimization: Implemented Google Analytics tracking and engagement monitoring, identified low-engagement features (report downloads, detailed links), deployed AppCues and re-education campaigns resulting in 40% weekly engagement rate
- KPI standardization & governance: Led cross-functional initiative to standardize KPI definitions and formulas across reports, dashboards, and ZMS platform, defined North Star metrics and essential KPIs for each campaign objective ensuring consistent measurement and decision-making
Deependra Pokhrel
Last position:
Data Specialist at Cloud Factory
- As a Data Specialist, I leveraged analytical expertise to transform raw data into actionable insights, driving strategic decision-making and operational improvements. My role encompassed data interpretation, reporting automation, and cross-functional collaboration, utilizing advanced tools such as Microsoft Excel, Power BI, and Python for comprehensive data analysis.
- Implemented Python scripts to validate and reconcile large datasets, reducing manual errors and improving data reliability.
- Utilized Python (Pandas, NumPy, Matplotlib/Seaborn) to automate data cleaning, analysis, and visualization, improving efficiency and accuracy in reporting.
- Developed interactive dashboards in Power BI to present key metrics, trends, and performance indicators, facilitating real-time decision-making.
- Designed and executed automated reports using Excel (Pivot Tables, Power Query, VBA) and Power BI, ensuring data accuracy and consistency across departments.
- Data Analysis: Excel (Advanced Pivot Tables, Power Query), Power BI (DAX, Data Modeling), Python (Pandas, NumPy, Visualization Libraries)
- Automation & Reporting: Power BI Dashboards, Excel Macros (VBA), Python Scripting.
Nikunjkumar Parmar
Last position:
Senior Java Backend Developer at Questax Professionals GmbH
- Provide the Price Listing Service Team Price for all cars and vans in different markets
- Adjust market-specific requirements like taxes, government subsidies, campaigns
- Import, synchronize and store new prices for all new and existing cars in Redis datastore
- Support our product and handle on-call duties
- Daily operations, developing new features, bug fixing
- Pair programming, code reviews, mob programming
- Develop POCs for new ideas
- Maintain and extend the backend
- DevOps tasks
- Perform Kubernetes updates
- Adjust and further develop Kubernetes resources
- Develop and customize Helm charts
- Adjust and update ArgoCD
- Maintain, adjust and further develop CI/CD pipelines
Meisam Ghafarlangroudi
Last position:
Senior AI Engineer / Data Scientist at Geeks Ltd (WordUp)
Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.
- Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
- Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
- Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
- Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
- Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.
Christian Richter
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Ilya Isakov
Last position:
Data/Platform/Software Engineer/SRE at IT Consulting
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
Henning Petersen
Last position:
Backend Systems Development at Deutsche Bank/DWS/Morgenfund
- Developed backend systems for the DWS Investment App, a white-label investment solution (robo-advisor), and an investment solution for institutional clients.
- Java 8-17, Kotlin, Spring Boot, Spring MVC, OpenAPI 3.0, JPA, JDBI, Oracle, Hazelcast, JXLS, Apache POI, Apache PDFBox, Apache Kafka & Avro, Active MQ, Elasticsearch, React Native, Spock Test, IntelliJ IDEA, Kubernetes, Helm, Microservices/Netflix-Stack, TeamCity, Splunk.
- Kanban team, continuous integration.
- Migrated existing applications from Deutsche Bank's private cloud environment to Azure as part of a carve-out.
Mario Ellebrecht
Last position:
Developer and Consultant at Freelancer
Discover over 15,000 top freelancers
Statistics of experts using Apache Hadoop
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
3 years (Germany: 2.8 years)
Positions per freelancer
8 (Germany: 12)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Professional Services, Retail
Certification focus areas
Information Technology, Project Management, Research and Development
Bachelor's degree or higher
90% (Germany: 95%)
Master's degree or higher
60% (Germany: 64%)
Doctorate
10% (Germany: 8%)
Certifications per freelancer
1 (Germany: 4)
Most common languages
German, English, Spanish
Speak two or more languages
92% (Germany: 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 Berlin 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 Berlin using Apache Hadoop
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 Hadoop is
Apache Hadoop is a framework for storing and processing very large data sets across clusters of standard machines. It is still used for batch analytics, data lake foundations, log processing, and long-running ETL jobs where distributed storage and parallel processing matter.
Core building blocks
- HDFS for distributed storage
- YARN for cluster resource management
- MapReduce for batch processing
- Common ecosystem tools such as Hive, Pig, Sqoop, and Oozie
- Integration with Spark and other data processing engines
Strong professionals know how these parts fit together and where each one adds value. They also understand when Hadoop should sit behind other tools instead of being the main processing layer.
Typical project work
Companies bring in Apache Hadoop specialists for platform setup, cluster tuning, data ingestion, job debugging, and migration planning. They are also used to stabilize old Hadoop stacks that still power reporting, archives, or compliance workloads in Berlin teams that work with large internal data sets.
When to hire help
- A cluster is slow, unstable, or costly to operate
- ETL jobs fail, overlap, or miss data quality checks
- HDFS storage layout needs redesign
- Hive queries or MapReduce jobs need performance work
- A move toward Spark, cloud storage, or modern lakehouse tools is starting
Freelance expertise is useful when the work is technical but not full time. It helps when a team needs a focused specialist for a migration, audit, rescue, or short implementation phase.
What strong specialists know
Good Apache Hadoop professionals understand storage layout, security basics, resource queues, and data flow across the stack. They write clear documentation, spot bottlenecks quickly, and can explain tradeoffs between Hadoop, Spark, Hive, and cloud-native alternatives without overselling one tool.
Working with Berlin teams
In Berlin, Hadoop work often fits teams in media, logistics, finance, and enterprise analytics. Remote collaboration is common for analysis and tuning, while on-site time can help during access reviews, incident response, or cluster transitions. Clear English is usually enough, but local coordination skills matter on larger internal projects.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Apache Hadoop.
Apache Hadoop is mainly used for storing and processing large data sets across distributed clusters. It supports batch analytics, log processing, data lake foundations, and ETL jobs that need horizontal scale. Many teams still rely on it for stable back-end data work.
Hadoop is often the storage and cluster layer, while Spark is the faster processing engine that many teams run on top of it. Compared with newer cloud data platforms, Hadoop can be more hands-on and infrastructure-heavy, but it is still strong for established batch systems and internal clusters. The right choice depends on your existing stack and migration path.
A strong Hadoop specialist usually knows HDFS, YARN, Hive, and sometimes Spark, Sqoop, or Oozie. Security, Linux administration, SQL, shell scripting, and log analysis are also common adjacent skills. Those skills help with tuning, debugging, and stable operations.
The needed depth depends on the work. A small Hive fix may only need a practical specialist, while cluster recovery, migration, or security hardening needs someone with deep platform experience. If the project touches production data, choose proven hands-on expertise over general familiarity.
Bring in Apache Hadoop help when the team needs focused support for a short period, such as a migration, performance issue, or platform audit. Freelance experts are also useful when the internal team knows the business data but lacks deep cluster knowledge. That is common in larger Berlin organizations with legacy data stacks.
Yes, much of the work can be done remotely because analysis, tuning, and troubleshooting are usually based on logs, configs, and access to the cluster. On-site time can still help for incident response, stakeholder workshops, or security-sensitive changes. Many Berlin teams use a hybrid setup.
Look for clear examples of production work with Hadoop clusters, not just training or lab experience. Good specialists can explain why a job failed, how they tuned storage or queues, and what they changed to improve reliability. They should also document their work in a way your team can maintain.
It can be, especially when you need reliable batch processing, distributed storage, or support for an existing data lake. For many new builds, teams compare it with Spark-first or cloud-native options before deciding. The best choice depends on data volume, operations effort, and how much legacy integration you have.
The average hourly rate of freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects is 92 €, which corresponds to a daily rate of about 736 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects, 90% hold at least a Bachelor's degree, 60% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects are German (100%), English (92%), and Spanish (23%).
The most common industries among freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects are Information Technology (92%), Professional Services (46%), and Retail (38%).
The most common business areas among freelancers in Berlin, Germany who have used Apache Hadoop in their recent projects are Information Technology (100%), Business Intelligence (85%), and Product Development (85%).
Main locations of FRATCH Experts, who have recently used Apache Hadoop
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.
Hamburg 
Munich 
Frankfurt 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!
Philipp Thomaschewski
FRATCH CEO
