
Apache Hive Experts in Germany
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Meet FRATCH Experts in Germany, 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.
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.
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
Giovanni L.
Last position:
Solution Architect at Nordea Bank
Consumer Cards Solution Architect
- Provided architectural leadership in Consumer Cards Domain establishing best practices and improving architectural transparency and maintainability by designing a structured documentation framework to enable reverse engineering of legacy card systems.
- Standardized architectural artefacts including BIAN Business Capabilities, UML diagrams in draw.io format (Use Case, Component, Sequence), naming conventions, document repository, design templates and blueprints, microservices.
- Produced high-level and low-level designs aligned with enterprise architecture governance processes and artefact standards.
- Provided architectural support to the Strategic Card Simplification Programme, focusing on card product migrations and application decommissioning across all countries. Agile environments (Scrum/SAFe).
- Analysed and designed AI use cases in the architecture domain.
Project: Payment Card Industry Data Security Standards (PCI DSS) Strategic Programme
- Analysed and documented existing data flows across card products and geographic regions to assess PCI DSS compliance.
- Identified areas involving sensitive data at rest and data in motion requiring encryption or masking, ensuring adherence to PCI DSS requirements.
- Collaborated with security, infrastructure, and application teams to align encryption strategies with regulatory and organizational policies.
- Provided strategic advisory services on data strategy, data governance, data management, data quality, data architecture, data mesh, MEGA HOPEX, DAMA-DMBOK, event-driven architecture, end-to-end data flows and card product harmonization models.
- Ensured solution design alignment with regulatory compliance (BCBS 239, DORA, GDPR) and internal policies.
Project: Denmark ATM Outsourcing Project
Objective: Outsource ATM operations and maintenance to a third-party provider while expanding the Denmark ATM fleet, with Nordea retaining ownership of ATMs and cash for the existing and extended infrastructure.
- Led a cross-functional delivery team (project management, business analysis, and architecture) and documented the as-is ATM ecosystem architecture, including end-to-end data flows, integrations, and internal/external application interfaces.
- Designed end-to-end processes for authorization, reconciliation, and settlement, aligning operating model, controls, and compliance requirements across Nordea and the outsourced service provider.
- Produced high-level and low-level solution designs using standardized UML artefacts (Use Case, Component, and Sequence diagrams) to support vendor onboarding, integration planning, and implementation.
- Ensured architectural alignment and decision-making across enterprise stakeholders and third-party providers, managing dependencies and interfaces in the context of the outsourcing initiative.
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
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
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.
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
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
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
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
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.
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%
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).
Discover over 15,000 top freelancers
Statistics of experts using Apache Hive
Aggregated from the professional profiles of matched freelancers.
Experience
19 years

Position duration
1.8 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, Product Development
Bachelor's degree or higher
94%
Master's degree or higher
68%
Doctorate
9%

Certifications per freelancer
4

Most common languages
German, English, Spanish

Speak two or more languages
97%
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 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 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 (87%)
- Banking and Finance (62%)
- Automotive (41%)
- Telecommunication (38%)
- Insurance (36%)
- Professional Services (36%)
- Retail (36%)
- Education (33%)
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 built for querying and managing large datasets stored in distributed systems. Its HiveQL language resembles SQL, allowing analytics teams to work with Hadoop data without writing every processing task in a lower-level framework. Hive is designed for batch analysis rather than low-latency transactional workloads.
Core data workflows
Hive supports structured data preparation, exploration and reporting across data lakes. Companies use it to create reusable tables, define schemas and run scheduled transformations over files in formats such as Parquet, ORC and Avro.
- Build external and managed tables
- Transform raw events into analytical datasets
- Partition and bucket data for efficient scans
- Schedule recurring warehouse queries
Ecosystem and tooling
Strong Apache Hive expertise includes the surrounding Hadoop ecosystem. Professionals often work with HDFS, YARN, Tez, Spark, Kafka and distributed SQL engines such as Presto or Trino. They also understand metastore design, JDBC or ODBC access, orchestration tools and cloud object storage.
In Germany, Hive-based estates may connect established enterprise data warehouses with newer lakehouse environments. Clear documentation and reliable communication matter when teams are split between local offices and remote specialists.
When companies need specialists
Freelance expertise is useful when a data platform needs modernization, faster queries or a controlled migration. It can also fill a gap during a large ingestion project, a Hadoop transition or the integration of Hive tables with reporting and machine learning workflows.
- Diagnose slow joins, scans and partition pruning
- Migrate schemas and workloads to cloud storage
- Establish data quality and lineage checks
- Connect Hive with BI and orchestration systems
Skills that distinguish experts
Effective professionals understand both SQL semantics and distributed execution. They choose suitable file formats, compression, partitions and table layouts instead of treating Hive like a conventional relational database. They can inspect execution plans, tune Tez or Spark settings and explain trade-offs to data owners.
Security is also part of the work. Useful experience includes access controls, encryption, metadata governance, monitoring and dependable recovery procedures across development and production environments.
Choosing the right fit
Look for evidence of delivered Hive warehouses, not only familiarity with the product name. Ask how the professional handled skewed data, changing schemas, small-file problems and workloads that needed a different engine. A strong fit can describe measurable operational improvements without hiding the limits of batch processing.
For remote collaboration, agree on repository access, deployment ownership, query review and incident communication early. On-site involvement may help with legacy Hadoop environments, while distributed teams can work effectively when architecture decisions and data definitions are recorded clearly.
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 distributed storage, especially data lakes and Hadoop environments. Companies use it for batch reporting, data preparation, historical analysis and recurring warehouse workloads rather than real-time transactions.
Apache Hive is closely associated with batch-oriented warehouse processing and the Hadoop ecosystem. Spark SQL can combine SQL with broader application logic, while Presto and Trino are often chosen for interactive federated queries; the right choice depends on latency, storage, workload shape and existing platform investments.
Apache Hive work commonly requires knowledge of HDFS, YARN, Tez or Spark, Linux, distributed storage and data orchestration. Experience with Kafka, cloud object storage, Parquet, ORC, metadata catalogs, BI tools and data governance can also be important.
Apache Hive projects need practical experience with distributed data, not just knowledge of HiveQL syntax. The complexity rises with data volume, legacy Hadoop dependencies, security requirements, query performance issues and the number of systems connected to the warehouse.
Apache Hive projects are often suitable for remote collaboration because schemas, queries, infrastructure definitions and documentation can be reviewed online. On-site work in Germany may still help when access to legacy systems, internal stakeholders or restricted environments is required, and language expectations should be agreed in advance.
Apache Hive expertise is best assessed through concrete examples of table design, partitioning, file-format choices and execution-plan analysis. Ask the professional to explain how they resolved data skew, small files, failed jobs or slow joins in a comparable environment.
Apache Hive remains relevant where organizations operate established Hadoop warehouses or need Hive-compatible metadata and SQL workflows. Newer lakehouse and cloud services may replace parts of its role, but migration decisions should account for existing schemas, schedules, governance and downstream dependencies.
Apache Hive specialists can deliver table and schema designs, optimized HiveQL, ingestion and transformation jobs, migration plans, orchestration workflows and operational documentation. They may also provide monitoring, data-quality checks, access-control guidance and recommendations for Spark, Trino or another complementary engine.
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 757 € 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, 68% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Germany who have used Apache Hive in their recent projects have 19 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 (97%), English (95%), and Spanish (21%).
The most common industries among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (87%), Banking and Finance (62%), and Automotive (41%).
The most common business areas among freelancers in Germany who have used Apache Hive in their recent projects are Information Technology (97%), Business Intelligence (90%), 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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