
Apache Hive Experts in Germany
for reliable data warehousing, matched in minutes with AIHire experts who design Hive data warehouses, optimize SQL queries on Hadoop and connect large-scale batch processing with Spark, Tez or cloud storage. FRATCH matches you quickly with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Germany, who have recently used Apache Hive
Umut G.
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.
Alexander Z.
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.
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.
Bardiya B.
Last position:
Data Scientist at Rewe Digital GmbH
Statistical Forecasting Algorithm
- Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
- Migration from R/On-premise to Python/Snowflake
- Productionalization on Snowflake in cooperation with data engineers & DevOps
Monitoring Dashboard
- Data engineering for preparation & provisioning of necessary data/resources on Snowflake
- Development & deployment of a Streamlit dashboard in Snowflake
ML-based Probabilistic Forecasting on Vertex AI
- Development of a ML-based probabilistic forecasting algorithm from scratch
- Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI
Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow
Aamir S.
Last position:
Founder at Self-Directed Project Work
- Building independent projects in the AI/developer tools space.
- Experimenting with product ideas, rapid prototyping, and go-to-market validation.
- Designing AI-native operating model—leveraging agentic pipelines, living context schemas, and rigorous eval harnesses to multiply individual contributor leverage and eliminate implementation bottlenecks.
Serge K.
Last position:
Data Scientist & 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
- Development of feature store and data synchronization between environments
- Data science: evaluation of different forecasting models, including CatBoost, Contextual Gamma and Random Forest; implementation of training pipelines using Kubeflow on Vertex AI; scaling and development of an event-driven interface using Kafka as a forecasting service; evaluation of MLFlow for model tracking and model registry
- Implementation of REST API using KeyCloak OAuth2 and OpenID (JWT)
- Monitoring: implementation of dashboards with Grafana, Prometheus, Mimir, Streamlit and Loki to monitor prediction metrics, GCP and Snowflake costs for pipelines, and system metrics
- Development of Copilot Agent Skills
Marc M.
Last position:
Freelance Data Specialist at BrightlySoftware – A Siemens Company
- Migration of customer data from a private cloud to AWS
- Optimizing data transformation jobs and migration from Talend to AWS Glue
- Automation of all migration steps
- Used technologies: AWS, Python, Lambda, CloudFormation, SQLServer, AWS Stepfunctions, Glue, PySpark
Maik S.
- Development of a new generation of Spring Boot microservices for an archiving system on OpenShift, monitoring, security analyses
Stack: Java, Spring Boot, Kafka, Vaadin, OpenShift 4.x, Maven, Artifactory, Jenkins, Git/Github, GitHub Copilot, GitOps, CI/CD, Kargo/ArgoCD
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
Ashkan Z.
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Basem E.
Last position:
Head of Cloud & AI at VxLabs GmbH
- Led cloud and data engineering organization, defining architecture strategy for next-generation data platforms
- Designed and delivered an automotive fleet data management system including scalable ingestion pipelines, signal catalog management, and campaign processing workflows
- Built cloud-native microservices and streaming architectures supporting real-time vehicle data and AI-powered threat detection
- Established engineering standards for data quality, security, lineage, and governance in alignment with ISO/SAE 21434 and GDPR
- Managed engineering teams across data, backend, cloud, and AI functions, ensuring consistent delivery of high-quality, production-ready solutions
Emmanouil T.
Last position:
Senior Analytics Engineer at Trade Republic Bank GmbH
- Implementation of analytics and automation solutions for the Anti Financial Crime business unit
- Providing the infrastructure, including reusable data models and feature ingestion for production ML and rule based models in the areas of Account Take-Over and Card fraud detection, as well as Customer Risk Assessment
- Tools used: Snowflake, dbt, Looker, AWS, Python, Airflow, Metaflow
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
Srikanth V.
Last position:
Safe Scrum Master at Brunel GmbH
- In an automotive environment, facilitated Agile adoption across 3 teams, improving sprint velocity by 25%
- Managed backlog, burndown charts and sprint planning for 40+ user stories
- Conducted risk analysis and implemented mitigation plans, reducing project delays by 30%
- Led retrospectives and demos, increasing stakeholder satisfaction scores by 15%
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
1.8 years

Positions per freelancer
13

Top business areas
Information Technology, Business Intelligence, Product Development

Top industries
Information Technology, Banking and Finance, Automotive

Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
94%
Master's degree or higher
64%
Doctorate
11%

Certifications per freelancer
4

Most common languages
German, English, Spanish

Speak two or more languages
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 Germany 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 Germany 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 29 Oct 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 (88%)
- Banking and Finance (61%)
- Automotive (39%)
- Professional Services (39%)
- Retail (39%)
- Telecommunication (37%)
- Education (34%)
- Insurance (32%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Data warehousing with Hive
Apache Hive is a data warehouse system built for querying and managing large datasets stored in distributed systems. Its SQL-like language, HiveQL, lets teams analyze data without writing every processing step in a low-level programming language. Hive commonly runs with Hadoop and integrates with object storage and modern data platforms.
Core architecture
Hive uses schemas, databases, tables, partitions and buckets to organize data for analytical workloads. The metastore stores table definitions and location details, while execution engines such as Tez or Spark run query plans. Strong specialists understand file formats including ORC, Parquet and Avro, along with compression, serialization and schema evolution.
Ecosystem and tooling
Hive expertise often connects several parts of the data stack:
- Configure the Hive Metastore and catalog structures
- Write and optimize HiveQL for batch analytics
- Use Hadoop HDFS, YARN and cloud object storage
- Work with Tez, Spark, Oozie or workflow orchestration tools
- Secure access with Kerberos, Ranger or cloud identity controls
Typical delivery work
Companies use Hive for reporting layers, historical analysis, log processing, data lake queries and scheduled transformation pipelines. Freelance specialists can build partitioned tables, migrate legacy warehouse workloads, tune joins and create reliable ingestion paths from operational systems. They may also connect Hive with BI tools or downstream machine learning workflows.
When companies need specialists
External expertise is useful when queries become slow, storage costs rise or a Hadoop-based warehouse needs to move to cloud infrastructure. It also helps during platform migrations, metastore repairs, data quality projects and security changes. In Germany, specialists may support teams across manufacturing, retail, logistics, research and other industries that operate large analytical environments.
What strong professionals bring
Quality work combines SQL fluency with a practical understanding of distributed execution. Strong professionals inspect query plans, choose suitable partitioning, manage small-file problems and validate results against source data. They communicate clearly with data teams and business stakeholders, document operational decisions and collaborate effectively on-site or remotely in Germany, with English or German depending on the project.
Frequently asked questions
Quick answers to the questions that come up most around Apache Hive.
Apache Hive is used to query, transform and organize large datasets in Hadoop-based data warehouses and data lakes. Teams use HiveQL for scheduled reporting, log analysis, historical processing and batch data preparation rather than low-latency transactional applications.
Hive is traditionally focused on SQL-driven batch warehousing and integrates closely with Hadoop storage and catalog services. Spark SQL often offers broader in-memory processing and application integration, while the right choice depends on workload patterns, existing infrastructure and operational requirements.
A strong Apache Hive specialist usually understands Hadoop HDFS, YARN, the Hive Metastore and distributed file formats such as ORC and Parquet. Experience with Tez, Spark, workflow orchestration, data security and cloud object storage is also valuable.
Hive work benefits from practical experience with production data volumes, partitioning, query plans and batch reliability. Ask for examples of warehouse migrations, performance tuning, data quality controls and incident resolution that match your system rather than relying only on certification claims.
Apache Hive projects can often be delivered remotely because query work, configuration and documentation fit well with distributed collaboration. On-site work may still help during secure-network access, platform cutovers or workshops, and teams should agree on language, access procedures and working hours in advance.
Evaluate whether an Apache Hive professional can explain execution plans, partition design, file formats and failure handling in clear terms. A practical review of a slow query or a sample warehouse design reveals more than a list of tools alone.
Hive is mainly designed for analytical and batch workloads, not direct transactional serving or strict real-time response requirements. A specialist should identify those constraints early and consider systems such as streaming platforms, operational databases or dedicated query engines alongside Hive.
Hadoop Hive is a common informal name for Apache Hive when it is used with the Hadoop ecosystem. It does not describe a separate product, although deployment details and available features can differ between older Hadoop installations and newer cloud or standalone environments.
The average hourly rate of freelancers in Germany who have used Apache Hive in their recent projects is 96 €, which corresponds to a daily rate of about 772 € based on an 8-hour working day.
Of the freelancers in Germany who have used Apache Hive in their recent projects, 94% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Germany who have used Apache Hive in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Germany who have used Apache Hive in their recent projects are German (98%), English (95%), and Spanish (20%).
The most common industries among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (88%), Banking and Finance (61%), and Automotive (39%).
The most common business areas among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (98%), Business Intelligence (85%), and Product Development (71%).
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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