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Apache Hadoop Experts in Munich

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Hire experts who build Hadoop data lakes, tune HDFS and YARN, and support MapReduce, Hive, and Spark workflows. Get fast, precise matching with vetted, available freelancers.

Meet FRATCH Experts in Munich, who have recently used Apache Hadoop

Verified expert

Philipp Grunert

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Machine Learning & Data Engineer

München
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
Verified expert

Christiane Neher

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Management Consultant

Munich
Christiane Neher

Last position:

Management Consultant at Christiane Neher Management Consulting

Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:

  • Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
  • Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
  • Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
  • Conceptual support for the development of an integrated reporting and performance management setup
  • Execution of customer insights analyses to identify patterns and anomalies within customer data clusters

Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:

  • Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
  • Strategic-operational consulting for the introduction of RELEX including best practices
  • Support in defining overarching goals and requirements (2-year target picture)
  • Guidance in scoping a relevant supply chain network segment for the project
  • Development of a roadmap for iterative, incremental RELEX setup and rollout
  • Assessment of project dependencies (interfaces, configurations, etc.)
  • Advice on prioritized implementation of business requirements and data interfaces
  • Support in test planning (data validation, system testing, UAT)
  • Consulting on internationalization, change management, training, and knowledge transfer
  • Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX

Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:

  • Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
  • Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
  • Proposal of quality improvements for program and modernization efforts
  • Sparring partner and professional, technical, structural and organizational consulting for project and program management

Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:

  • Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
  • Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
  • Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
  • MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)

Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:

  • Coaching of the core team with topic managers and team leads
  • Introduction to the OKR topic and setup of the OKR cycle
  • Establishment of the OKR approach in teams and on a cross-team level

Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:

  • Analysis of current challenges
  • Definition of overarching goals
  • Development of a proposal for a new team structure
  • Identification of required competencies, skills and responsibilities
  • Advisory and alignment on communication and change management strategy
Verified expert

Valery Khamenya

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AdTech Engineer & Data Scientist

Munich
Valery Khamenya

Last position:

Sr. Data Scientist & Engineer at Virtual Minds

  • Development of high-performance ad distribution via auction
  • Holistic (multi-campaign & multi-channel) advertisement placement optimization
  • Algorithmic optimization for NP-Hard/NP-e
  • Multiple Knapsack Problem with constraints
  • Online estimation of parameters in stochastic environments

Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker

Verified expert

Serge Kalinin

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MLOps (machine learning operations)

Munich
Serge Kalinin

Last position:

MLOps (machine learning operations) at REWE Digital GmbH

  • It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
  • GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
  • Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
  • CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Verified expert

Florian B.

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Digital Transformation Manager

Florian B.

Last position:

Business Architect — Project Organization Blueprint for Restructuring

Tasks & results:

  • Worked out measures to improve management control during a restructuring program (approx. 80 people involved)
  • Set up PMO to enforce transparency, reporting, and data-driven decisions
  • Built an integration template to move team silos (software, field installation, supply chain) into an overarching project structure with lean tracking systems for timeline, progress, and KPIs
  • Technologies / methods: PMO setup, KPI tracking, project organization, Jira, Confluence
Verified expert

Christian Schulz

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Data-Scientist/AI Engineer

Ismaning
Christian Schulz

Last position:

Data-Scientist/AI Engineer at The Marcom Engine GmbH & Co. KG

  • Concept creation and implementing AI Agents in AWS Cloud
  • Continuously alignment with stakeholders
  • Collaborate with DevOps
  • Technologies: Git, CI/CD (GitHub Actions), Python/ML, Streamlit, Deno/typescript, AWS SAM, AWS Bedrock, AWS Lambda, AWS Dynamo DB, AWS S3, AWS Event Bridge etc.
Verified expert

Stephan Sahm

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Senior Data/ML Consultant & Technical Lead

München
Stephan Sahm

Last position:

Senior Data/ML Consultant & Technical Lead at Jolin.io

  • Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)

  • Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)

  • Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)

  • Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)

  • Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)

Verified expert

Maziyar Khorrami

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Senior Data Engineer

Taufkirchen
Maziyar Khorrami

Last position:

Data Engineer at MSD Germany

  • Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
  • Performance Optimization of Data Ingestion of ETL Pipeline
  • Development of Data Validation using Great Expectations
  • Leading of the data migration for two sources exchanges
  • Data Modeling in AWS Redshift

MLOps

  • Model inference implementation by mlflow and AWS SageMaker
  • Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
  • Implementatino of Model Registry and artifactory using mlflow
  • Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
  • Feature importance using mlflow

Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy

Verified expert

Biju Krishnan

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Freelance AI Strategist & Governance Expert

Munich
Biju Krishnan

Last position:

Freelance AI Strategist & Governance Expert at DataSiens Freelancer

  • Developed the AI strategy for a major Austrian retailer with over €10 billion in annual revenue.
  • Developed a go-to-market strategy for AI services for a Norwegian consulting firm specializing in SAP technologies.
  • Delivered AI for Business training programs to a leading German supermarket chain.
  • Defined AI governance project structure and roadmap for a large German manufacturer.
  • Certified facilitator for AI Design Sprintâ„¢, leading use case discovery workshops for large enterprises.
  • IEEE Certified AI Ethics Assessor with expertise in building AI governance frameworks aligned with the EU AI Act.
  • Founder of aiethicsassessor.com as knowledge base for AI governance and AI legislation.
  • Author of a best-selling Udemy course on Data Architecture.
  • Developed intelligent agents using low-code/no-code platforms to automate complex business processes.
Verified expert

Eyasu Habte

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Data Scientist

München
Eyasu Habte

Last position:

Data Scientist at Deutsche Bundesbank

  • Developed web scraping scripts to extract and parse over 5000 product data from the Zalando website.
  • Performed ETL processes using Apache Spark in CDSW, loaded the data into the Hadoop ecosystem (HDFS), and managed data using Hive and Impala.
  • Implemented machine learning algorithms, achieving 85–90% accuracy on multi-class product classification.
  • Integrated Zalando's product and price data into the dashboard with Otto and Takko for interactive visuals.
Verified expert

Anton Klonov

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Head of Technical Overall Integration NSC / Hadoop Cloud Development

Munich
Anton Klonov

Last position:

Head of Technical Overall Integration NSC / Hadoop Cloud Development at IABG

  • Head of technical overall integration NSC (National Secure Cloud project with about 60 employees).

  • Technical integration of all subprojects into one product, definition of interfaces, basic components of a cloud including hardware, technical architecture of the IABG base.

  • Development of a Cloud Management Platform (CMP) that can create a private/mixed cloud of any complexity based on a textual description with one click or interactively.

  • CMP also includes the complete hardware management cycle.

  • As a foundation, it uses Kubernetes, OpenStack, and Hadoop.

  • The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are automatically configured.

  • The private cloud can run any customer workloads, including a full Hadoop stack with HDFS, Spark, MapReduce, Mesos, HBase and around 20 other ML/DL technologies.

  • Hadoop worker clusters can also be automatically installed on bare metal or commodity hardware without Kubernetes.

  • OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.

  • Development of a Java application Rudi: SOAP, REST, containers, database.

  • Technologies: Kubernetes (K3s, RKE2, Minikube, Harbor, Gitea, Jenkins, Longhorn, Keycloak, Rancher), OpenStack (Nova, Neutron, Keystone, Swift, Ceph, Cinder, Sahara, Magnum, Kayobe, Kolla, Bigrost, Ironic), Hadoop (HDFS, Ambari, Solr, Livy, Ranger, YARN, Tez, HBase, Kafka, Hive, Zookeeper, MapReduce, Spark, Oozie, Flink), virtualization (Kubernetes (K3s), VMware, Oracle), scripting (Ansible, Puppet, Juju, Shell, Groovy, Gradle, Maven).

Verified expert

Josef Schermer

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DevOps

Munich
Josef Schermer

Last position:

DevOps at Software house for an industrial company

  • Implementation, maintenance and operation of an ERP system and a document exchange platform for a corrugated cardboard manufacturer.
  • Tools and systems: Unix (Debian 6.x), C, SVN, Windows, C#, MS SQL Server, SCRUM.

Discover over 15,000 top freelancers

Statistics of experts using Apache Hadoop

Aggregated from the professional profiles of matched freelancers.

Experience

21 years (Germany: 18 years)

Position duration

2 years (Germany: 2.8 years)

Positions per freelancer

16 (Germany: 12)

Top business areas

Business Intelligence, Information Technology, Product Development

Top industries

Information Technology, Banking and Finance, Professional Services

Certification focus areas

Information Technology, Business Intelligence, Product Development

Bachelor's degree or higher

100% (Germany: 95%)

Master's degree or higher

69% (Germany: 64%)

Doctorate

8%

Certifications per freelancer

3 (Germany: 4)

Most common languages

German, English, Spanish

Speak two or more languages

100% (Germany: 98%)

Based on our profile pool as of 30 Aug 2026.

Daily rate distribution

0 2 4 6 8
<€640 €640-​800 €800-​960 €960-​1120 €1120+

The chart shows how the daily rates of freelancers in this technology in Munich 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 Munich using Apache Hadoop

Rates are based on recent contracts and do not include FRATCH margin.

1000
750
500
250
Rate comparison chart
Daily rate avg. 856 €
Germany avg. 788 €

The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.

1000
750
500
250
Rate comparison chart
Median rate 880 €
Germany median 800 €

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

Hadoop basics

Apache Hadoop is a distributed system for storing and processing very large data sets across clusters of commodity servers. Companies use it when data volume, batch processing, and fault tolerance matter more than low-latency response. It often sits in the middle of broader data platforms.

Core pieces

  • HDFS for distributed storage
  • YARN for cluster resource management
  • MapReduce for batch processing
  • Hive for SQL-style analysis
  • Spark alongside Hadoop for faster processing

These pieces are often combined with Kerberos, Sqoop, Kafka, and workflow tools to move and secure data across the stack.

Typical work

Strong specialists design data pipelines, manage cluster capacity, and keep jobs reliable in production. They also handle upgrades, permissions, performance tuning, and integration with BI or analytics layers. In Munich, this work often supports finance, industry, travel, and data-heavy enterprise teams.

When to bring help

  • A cluster is slow, unstable, or hard to scale
  • Batch jobs fail or miss service windows
  • Data needs to move from legacy systems into Hadoop
  • Security, access control, or audit requirements have grown
  • Hive, Spark, or HDFS issues block delivery

Freelance help is useful for migrations, rescue work, platform hardening, and short-term delivery peaks.

What good experts know

Good Hadoop professionals understand data layout, job design, and the trade-offs between storage, compute, and network use. They write clear runbooks, explain cluster behavior well, and work safely with sensitive data. They also know when Hadoop is the right tool and when another engine fits better.

Ecosystem fit

Hadoop rarely stands alone. It is often part of a stack with Hive for querying, Spark for processing, Oozie or Airflow for orchestration, and cloud object storage in hybrid setups. Companies looking for Apache Hadoop support in Munich often want experts who can work remotely, align with English-speaking teams, and still fit local on-site needs when required.

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Frequently asked questions

Need clarity? These are the questions we hear most often about Apache Hadoop.

A strong Apache Hadoop specialist helps with cluster setup, HDFS storage, YARN resource handling, and batch data pipelines. They also support Hive queries, Spark integration, and production troubleshooting when jobs fail or slow down.

Hadoop is often the better fit when durable distributed storage matters as much as processing. Spark can run on top of Hadoop, but Apache Hadoop still matters for HDFS, cluster management, and large batch workflows that need a stable storage layer.

Good Apache Hadoop specialists usually know Linux, shell scripting, SQL, and at least one processing layer such as Hive or Spark. They should also understand cluster security, data ingestion, scheduling, and how storage formats affect performance.

It depends on the scope, but production work needs someone who has already handled real clusters, failures, and upgrades. For Apache Hadoop, theory is not enough; the expert should have hands-on experience with data pipelines, access control, and operational support.

Yes. Many Apache Hadoop tasks can be handled remotely, especially analysis, job tuning, migration planning, and support. On-site time can still help when a company needs access to internal systems, sensitive data, or close coordination with local teams in Munich.

Ask for concrete examples of clusters they have stabilized, pipelines they have improved, and problems they have solved. A good Apache Hadoop professional explains trade-offs clearly, documents changes well, and can talk about HDFS, YARN, Hive, and Spark without vague claims.

Yes, especially in environments with large batch workloads, long-running storage needs, or existing platform investments. Hadoop often appears in hybrid stacks where Spark, Hive, Kafka, and cloud storage work together rather than replacing each other.

Prepare a clear view of your cluster setup, data sources, job failures, security needs, and business deadlines. For Apache Hadoop work, the best results come when the specialist can review logs, architecture diagrams, and pipeline ownership before starting.

The average hourly rate of freelancers in Munich, Germany who have used Apache Hadoop in their recent projects is 107 €, which corresponds to a daily rate of about 856 € based on an 8-hour working day.

Of the freelancers in Munich, Germany who have used Apache Hadoop in their recent projects, 100% hold at least a Bachelor's degree, 69% hold at least a Master's degree, and 8% hold a doctorate.

On average, freelancers in Munich, Germany who have used Apache Hadoop in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 2 years.

The most common languages among freelancers in Munich, Germany who have used Apache Hadoop in their recent projects are German (100%), English (100%), and Spanish (29%).

The most common industries among freelancers in Munich, Germany who have used Apache Hadoop in their recent projects are Information Technology (93%), Banking and Finance (79%), and Professional Services (64%).

The most common business areas among freelancers in Munich, Germany who have used Apache Hadoop in their recent projects are Business Intelligence (100%), Information Technology (93%), and Product Development (79%).

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.

Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg

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