Apache Hive Expert in Germany
in minutes from over 15,000 CVs with the power of AI.Work with specialists who design robust data warehousing solutions, optimize complex HiveQL queries, and manage massive datasets on distributed storage. Our AI-driven platform connects you with vetted, available freelance professionals in Germany who are ready to streamline your big data architecture immediately.
Meet FRATCH Experts in Germany, who have recently used Apache Hive
Thomas Müller
Last position:
Requirements Engineer (SPC) - ONE.CRM VW Salesforce Solution at CARIAD SE / Diconium Strategy GmbH
- Rework demand, development and operational organizational set up for the Solution Train
- Rework requirement refinement process flow from strategic theme to user story
- Introduction of visualization tools (Canvas) of work dependencies over different requirement levels and Solution Train leadership coaching
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.
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
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.
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
Marc Matt
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
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
Tan Pham
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Roland Glienke
Last position:
Scrum Master SAFe Payments at Kreditanstalt für den Wiederaufbau
- SAFe Scrum Master for two delivery teams in the payments area
- Successful preparation of the teams for PI Plannings
- Moderation of events and synchronization across team boundaries
- Early identification of risks and blockers and support in removing them
- Structured facilitation of Scrum events using Jira dashboard/Scrum and Kanban board
- Coaching and support of the Product Owner in refinement, building objectives, and managing the product backlog
- Operationalization of the DevOps integration of operations staff into cross-functional teams
- Introduction of a compliance-compliant role and authorization model to meet regulatory requirements
- Collaboration with IAM and business departments
- Facilitation of all Scrum events, continuous process improvement, and handling of impediments
Emmanouil Tzouridis
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
Basem Elasioty
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
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.
Srikanth Vajja
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%
Matthias Lang
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
Benjamin Tsapfack
Last position:
Test Manager and Software and Hardware Tester at Deutsche Bahn
- Developing test strategy: Designing and implementing a comprehensive test strategy for digital rail projects.
- Defining test approaches: Establishing and documenting methodical test approaches to maximize coverage and efficiency.
- Team management: Assigning roles and responsibilities within the test team to ensure effective and goal-oriented test execution.
- Setting test principles to ensure test integrity and quality.
- Integration and system testing based on specific specifications and standards.
- Infrastructure development for automated test environments, including test systems and test patterns.
- Testing Yemba event detection algorithms in a vehicle data logger using generative artificial intelligence.
- Test case development for internal purposes and for partner companies (device manufacturers).
- Performance and load testing to ensure system stability and scalability.
- Ensuring compliance with relevant standards such as CENELEC, EN50126 and EN5012.
Discover over 15,000 top freelancers
Statistics of experts using Apache Hive
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
1.9 years
Positions per freelancer
14
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
90%
Master's degree or higher
65%
Doctorate
6%
Certifications per freelancer
4
Most common languages
German, English, Spanish
Speak two or more languages
97%
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 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Distributed data warehousing at scale
Apache Hive is a distributed data warehouse system built on top of Apache Hadoop. It facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. This technology allows organizations to project structure onto largely unstructured data, enabling scalable data analysis across massive commodity clusters.
How enterprises leverage the data warehouse
Companies utilize this technology to run complex analytical queries over petabytes of information. It serves as a foundational layer for business intelligence, reporting, and historical data analysis.
- Building enterprise-scale data lakes and warehouses
- Transforming raw unstructured data into structured schemas
- Running long-running batch processing and ETL jobs
- Enabling ad-hoc querying for data analysts using SQL syntax
The big data ecosystem integration
The technology operates within a wider ecosystem of data engineering tools. Specialists seamlessly integrate it with resource managers like YARN, execution engines like Apache Tez, and storage layers like HDFS or Amazon S3. It also connects directly to visualization tools and BI suites through JDBC and ODBC drivers.
When to bring in external platform expertise
Setting up and tuning large-scale data warehouses requires specialized knowledge that in-house teams often lack. Freelance specialists assist when query performance degrades, cluster resources are misallocated, or during major migration projects. They provide immediate, hands-on experience to resolve bottlenecks without long-term overhead.
What defines a skilled data engineer
A proficient professional possesses deep knowledge of distributed systems and query optimization techniques. They understand partition pruning, bucketing, and vectorization to minimize execution times.
- Proficiency in writing highly optimized HiveQL queries
- Hands-on experience with file formats like ORC and Parquet
- Deep understanding of the Hive Metastore architecture
- Experience migrating legacy warehouses to modern cloud storage
Navigating big data projects in Germany
German enterprises, particularly in finance, automotive, and logistics, require strict compliance with data privacy regulations like GDPR. Local freelance specialists understand how to set up secure data environments using Apache Ranger and Apache Atlas. They collaborate effectively with internal IT departments, ensuring that on-site or remote configurations meet high national security and performance standards.
Frequently asked questions
Quick answers to the questions that come up most around Apache Hive.
Apache Hive is primarily used for data warehousing, ETL pipelines, and analyzing massive datasets stored in distributed environments. It translates SQL-like queries into execution jobs, allowing data analysts to query Hadoop clusters without writing complex MapReduce code. This makes it ideal for historical reporting, data summarization, and ad-hoc analysis of large enterprise data lakes.
While both process big data, Apache Hive is designed as a traditional data warehouse system optimized for batch processing, whereas Spark is an in-memory data processing engine. Hive is traditionally slower but excellent for long-running batch jobs and structured data warehousing. Modern setups often use them together, utilizing Hive for metadata storage and Spark for fast, interactive analytics.
The automotive, banking, and logistics sectors in Germany rely heavily on Apache Hive to process immense volumes of operational and sensor data. Because these industries deal with legacy infrastructures and strict data residency laws, local specialists help them maintain robust on-site data warehouses. This ensures compliance with local guidelines while maximizing the value of their historical data assets.
Yes, migrating from an on-premises Apache Hive setup to cloud services like Amazon EMR, Google Dataproc, or Azure HDInsight is a common project type. Freelancers can migrate the physical data as well as the metadata stored in the Hive Metastore. This transition allows organizations to scale storage and compute independently while maintaining their existing SQL query infrastructure.
A well-rounded Apache Hive specialist usually has deep expertise in Hadoop, HDFS, and execution engines like Tez or MapReduce. They should be proficient in file optimization formats such as Parquet and ORC, and have a strong command of SQL. Understanding security frameworks like Apache Ranger and workload orchestration tools like Apache Airflow is also highly beneficial.
No, Apache Hive is fundamentally designed for batch processing rather than real-time data streaming. For real-time applications, companies usually combine it with streaming technologies like Apache Kafka or Apache Flink. Hive then acts as the final destination for cold storage and deep historical analysis rather than the immediate ingestion engine.
Most Apache Hive specialists in Germany work remotely, accessing secure staging environments through VPNs. However, critical phases like the initial architecture design or security audits often benefit from occasional on-site workshops. German language skills are frequently preferred for smooth integration with internal IT security teams and business stakeholders.
When evaluating a candidate, focus on their practical experience with performance tuning, partition strategies, and query optimization within Apache Hive. Ask how they resolve common issues like data skew, container sizing, or resource preemption on shared clusters. A strong specialist should be able to explain how they reduced execution times or cloud infrastructure costs in previous assignments.
The average hourly rate of freelancers in Germany who have used Apache Hive in their recent projects is 95 €, which corresponds to a daily rate of about 756 € based on an 8-hour working day.
Of the freelancers in Germany who have used Apache Hive in their recent projects, 90% hold at least a Bachelor's degree, 65% hold at least a Master's degree, and 6% hold a doctorate.
On average, freelancers in Germany who have used Apache Hive in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Germany who have used Apache Hive in their recent projects are German (100%), English (94%), and Spanish (25%).
The most common industries among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (86%), Banking and Finance (61%), and Automotive (47%).
The most common business areas among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (97%), Business Intelligence (94%), and Product Development (72%).
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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