
Apache Hive Experts in Munich
matched in minutes by AIHire experts who design Hive data warehouses, optimize SQL workloads on Hadoop and connect batch analytics with modern lakehouse tooling. FRATCH matches you precisely with vetted, available freelancers for fast project support.
Meet FRATCH Experts in Munich, who have recently used Apache Hive
Michael N.
Last position:
Senior AI Engineer | Forward Deployed Engineer at Tiefbau
- Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
- Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
- Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.
Christiane N.
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
Serge K.
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
Christian S.
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.
Matthias L.
Last position:
Typescript Fullstack Engineer at Card Complete / Bank Austria
- Designed and developed the "Credit Risk Engine" using Camunda, Node.js and Typescript
- Greenfield project for credit card credit assessment for existing and new customers, including EBA KPIs, SCHUFA and CRIF scorings
- Built and modeled workflows (BPMN) and decision logic (DMN) with Camunda Modeler in close collaboration with stakeholders
- Implemented service tasks, user tasks and jobs with Nest.js, Node.js and Typescript, including exception handling
- Backend-for-Frontend (BFF), frontend with React, Tailwind and Ant Design UI library
- CI/CD with GitLab, Kubernetes/Rancher
Anton K.
Last position:
Head of Overall Technical Integration NSC / Hadoop Cloud Development at IABG
Head of overall technical integration NSC (National Secure Cloud, project with approx. 60 employees).
Technical integration of all subprojects into one product, definition of interfaces and basic components of a cloud including hardware, technical architecture of the IABG platform.
Development of a Cloud Management Platform (CMP) capable of creating private/mixed clouds of any complexity based on a textual description with one click or interactively.
CMP also includes the complete hardware management lifecycle.
Kubernetes, OpenStack and Hadoop are used as the foundation.
The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are configured automatically.
Private cloud can run any customer workloads, including a full Hadoop layer with HDFS, Spark, MapReduce, Mesos, HBase and around 20 additional ML/DL technologies.
Hadoop worker clusters can also be installed automatically without Kubernetes on bare metal or commodity hardware.
OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.
Development of a Java application Rudi: SOAP, REST, containers, DB.
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).
Stephan S.
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)
Maziyar K.
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
Eyasu H.
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.
Satish K.
Last position:
Sustainability Intern at Forschungszentrum Jülich GmbH
- Developed energy estimation models to estimate electric charging and hydrogen refueling requirements at charging and refueling stations for logistics trucks in Germany.
- Estimated future freight traffic demand for Germany using an in-house transport demand model.
- Designed a network of electric charging and hydrogen refueling stations based on transport model results, supporting data-driven infrastructure planning.
Josef S.
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 Hive
Aggregated from the professional profiles of matched freelancers.
Experience
18 years

Position duration
1.4 years

Positions per freelancer
16

Top business areas
Business Intelligence, Information Technology, Product Development

Top industries
Information Technology, Banking and Finance, Education

Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
90%
Master's degree or higher
80%
Doctorate
10%

Certifications per freelancer
3

Most common languages
German, English, Spanish

Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
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 Hive
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Apache Hive 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 (82%)
- Banking and Finance (73%)
- Education (55%)
- Automotive (45%)
- Insurance (45%)
- Professional Services (45%)
- Government and Administration (45%)
- Retail (45%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Apache Hive does
Apache Hive is a data warehouse system for querying and managing large datasets stored in distributed systems. Its HiveQL language gives teams a SQL-style way to run batch analytics without writing every distributed processing step by hand. It is commonly associated with Hadoop and enterprise data platforms.
Typical data workloads
Hive is suited to structured and semi-structured data processing where throughput matters more than interactive response times. Companies use it for governed reporting, historical analysis, transformation pipelines and large-scale aggregation across data lakes.
- Build analytical tables from raw event and transaction data
- Create repeatable ETL and ELT workflows
- Prepare datasets for reporting and machine learning
- Manage partitions, schemas and table metadata
Ecosystem and tooling
Strong Apache Hive specialists understand the systems around it, not only HiveQL. Relevant skills include Hadoop Distributed File System, YARN, Tez, Spark, MapReduce, Apache Parquet, ORC, Apache Avro and the Hive Metastore. Experience with Apache Oozie, Airflow, cloud object storage and lakehouse platforms is also valuable.
When companies need expertise
Freelance expertise helps when a data platform is slow, difficult to operate or being moved to a new architecture. In Munich, specialists may support manufacturing, insurance, mobility, retail and research teams while coordinating remotely or on site with data and business stakeholders.
- Reduce inefficient scans and expensive joins
- Plan migrations from legacy Hadoop environments
- Improve partitioning, file formats and table design
- Connect Hive workloads with cloud data services
What strong specialists deliver
Experienced professionals inspect execution plans, data distribution and storage formats before changing queries. They set practical standards for schema evolution, access control, metadata quality and pipeline observability. They also explain trade-offs clearly to teams that use SQL but do not maintain the underlying cluster.
Choosing the right fit
Look for evidence of production data platforms, not only familiarity with HiveQL. A good specialist can describe workload patterns, failure recovery, resource management and the limits of batch processing. For Munich projects, clarify expectations for German or English communication, on-site collaboration and access to sensitive data before work begins.
Frequently asked questions
Before you brief your next project: the most common questions about Apache Hive.
Apache Hive is used to query, transform and manage large datasets in distributed storage with a SQL-style language called HiveQL. It is a strong fit for batch reporting, data preparation, historical analysis and warehouse workloads.
Apache Hive focuses on SQL-based data warehousing and batch execution, while Spark SQL runs within the broader Apache Spark processing engine. The right choice depends on existing infrastructure, latency needs, transformation complexity and the skills already available on the team.
A strong Apache Hive specialist usually understands Hadoop Distributed File System, YARN, Tez, Spark and the Hive Metastore. Knowledge of Parquet, ORC, cloud storage, workflow orchestration and data governance is also useful.
The required background depends on the workload and its operational risk. A straightforward query or table change may need focused SQL and data-modeling skills, while cluster migrations and performance issues call for a professional who has operated distributed data platforms in production.
Yes. Apache Hive work is often handled remotely when documentation, secure access and clear ownership are in place. Munich teams should define whether occasional on-site workshops are needed and whether collaboration will take place in German, English or both.
Apache Hive can remain practical when a company already operates Hadoop-based storage, needs close control over data processing or runs substantial batch workloads. A cloud-native warehouse may be preferable when the priority is managed operations, fast interactive queries and minimal platform maintenance.
Ask the specialist to explain how they would diagnose a slow query, choose a file format and design partitions for changing data. High-quality Apache Hive professionals discuss execution plans, data skew, resource use, schema evolution and recovery rather than promising that every issue can be solved with query syntax.
Before starting with Apache Hive, clarify the storage layer, execution engine, metastore setup, security model and workload schedule. Also confirm whether the assignment covers query development, platform operations, migration, governance or performance tuning, since each area requires different preparation.
The average hourly rate of freelancers in Munich, Germany who have used Apache Hive in their recent projects is 97 €, which corresponds to a daily rate of about 779 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Apache Hive in their recent projects, 90% hold at least a Bachelor's degree, 80% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Munich, Germany who have used Apache Hive in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 1.4 years.
The most common languages among freelancers in Munich, Germany who have used Apache Hive in their recent projects are German (100%), English (91%), and Spanish (27%).
The most common industries among freelancers in Munich, Germany who have used Apache Hive in their recent projects are Information Technology (82%), Banking and Finance (73%), and Education (55%).
The most common business areas among freelancers in Munich, Germany who have used Apache Hive in their recent projects are Business Intelligence (91%), Information Technology (91%), and Product Development (82%).
Main locations of FRATCH Experts, who have recently used Apache Hive
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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