Apache NiFi Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Apache NiFi
Panagiotis Tsafaridis
Last position:
Senior Data Engineer Consultant at GOLDNER GmbH
- Onboarded and conducted comprehensive documentation and system analysis to assess the existing data infrastructure, facilitating rapid integration and collaboration across functional data teams (modelling, processing, reporting).
- Collaboratively defined the architecture and project structure for a central data pipeline repository, including hierarchical standards, knowledge management strategies, and role-specific responsibilities, enhancing maintainability and onboarding speed.
- Evaluated and validated open-source data routing tools (Airbyte, Apache NiFi, Dragster) for ingest and sync requirements in retail analytics, including local benchmarking and error-state testing.
- Led the design and deployment of Airbyte in Kubernetes, creating customized Helm charts, securing secrets handling, and configuring Ingress with TLS and internal DNS routing, ensuring full API and UI accessibility.
- Troubleshot and resolved Ingress controller issues, iterating through multiple stages of debugging and testing, and documented setup and replication steps for scalable reuse.
- Mapped data models to ARTS standard, supporting schema alignment for ERP and reporting use cases, and coordinated review loops to align future data processing logic.
- Drafted strategic 1-pagers comparing MinIO, Pub/Sub, and routing architectures, providing technical guidance for architectural decisions and investment planning.
- Enabled secure access and authentication mechanisms, including initial evaluation for SAML integration, cluster-level configuration reviews, and service annotation improvements.
Jorge Machado
Last position:
Technical Lead / Fractional CTO at Würth GmbH
I designed and developed an AI-powered multi-tenant platform on Azure that transforms SAP process recordings into technical documentation, presentations and automated tests, processing over 15,000 process recordings for enterprise customers like Würth. I owned the architecture, the production releases and the DevOps setup. I also designed a multi-tenant system with SSO and role-based access on Azure. Implemented an MCP Server with Dynamic OAuth Authentication.
Main Tasks:
- Sprint planning and feature preparation
- Design the multi-tenant platform architecture (FastAPI, SQLAlchemy, PostgreSQL row-level security for tenant isolation)
- Develop AI pipelines with Prefect for transcription (Azure Speech API), document generation and SAP screen-recording analysis (Claude, gpt-4-mini)
- Design and implement an MCP server to expose tenant knowledge to LLM clients (Claude), with async retrieval and reranking
- Implement LLM cost tracking, rate limiting and client pooling for Anthropic/OpenAI/Azure OpenAI endpoints
- Set up CI/CD: Docker images to Azure Container Registry, GitHub Actions, Azure Static Web Apps, Alembic migrations in containers
- Manage production releases and execute live data migrations for enterprise customers
- Define engineering standards and architecture patterns for the team
Environment: Azure / Azure Foundry / Python / FastAPI / Prefect / React / PostgreSQL
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
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Worked out measures to improve management control during a restructuring program (approx. 80 people involved)
- Set up PMO to enforce transparency, reporting, and data-driven decisions
- Built an integration template to move team silos (software, field installation, supply chain) into an overarching project structure with lean tracking systems for timeline, progress, and KPIs
- Technologies / methods: PMO setup, KPI tracking, project organization, Jira, Confluence
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
Lazaros Koutsianos
Last position:
RAG Webinar: Deep Dive and Use Cases at SHI GmbH
- Design, preparation and delivery of a webinar on 'RAG in Practice: How publishers create real value with AI'
- Preparing technical and strategic content on Retrieval Augmented Generation (RAG) for a mixed audience from the publishing industry
- Presenting specific use cases, technical backgrounds, common challenges and solution approaches when using RAG
- Providing practical insights into data preparation, model selection and output optimization in the context of digital publishing portals
- Conceptual and technical preparation of the webinar
- Selecting and presenting practical use cases from the publishing environment
- Developing technical backgrounds for implementing RAG systems
- Presenting and explaining typical challenges and solution strategies
- Large Language Models (LLMs)
- Retrieval Augmented Generation (RAG)
Manuel Schneider
Last position:
Project Manager at Univention
Industry: digital sovereignty, public sector
Content:
- Project steering (teams: consulting, development, testing, deployment/operations)
Products and standards:
- Jira, Confluence, Asana, Miro, Mural
- Open Source, Keycloak, Open Xchange, ownCloud
Bianca Schlüter
Last position:
Consultant OpenSearch at SHI GmbH
- Optimizing the online shop search function based on Magento and OpenSearch
- Advising on eliminating search pain points (composite search, case-insensitive search)
- Data modeling of products (parent) and items (child)
- Workshops to convey domain-specific search understanding
Lars B.
Last position:
xRM Solution Architect at Energiekonzepte Deutschland GmbH
- Requirements engineering and technical specifications
- System architecture consulting
- Designing the customer journey
- Defining APIs and integrating data
- Leading the development team/delivery unit
- Customer portal and customer app
- Partner management and field service app
Stephan Sahm
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Maziyar Khorrami
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Alain Gérard Ename
Last position:
Business Analysis / Requirements Engineering at 1&1
- Creating the functional specification for a dashboard solution for E2E management in the 5G deployment team in an Open RAN architecture
- Developing dashboards and reports with Power BI Desktop (data connection using Power Query, KPI calculations with DAX, publishing to Power BI Service)
- Developing solutions with Power Apps
- Integrating Power BI reports into Dynamics 365 Business Central
Anton Klonov
Last position:
Head of Technical Overall Integration NSC / Hadoop Cloud Development at IABG
Head of technical overall integration NSC (National Secure Cloud project with about 60 employees).
Technical integration of all subprojects into one product, definition of interfaces, basic components of a cloud including hardware, technical architecture of the IABG base.
Development of a Cloud Management Platform (CMP) that can create a private/mixed cloud of any complexity based on a textual description with one click or interactively.
CMP also includes the complete hardware management cycle.
As a foundation, it uses Kubernetes, OpenStack, and Hadoop.
The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are automatically configured.
The private cloud can run any customer workloads, including a full Hadoop stack with HDFS, Spark, MapReduce, Mesos, HBase and around 20 other ML/DL technologies.
Hadoop worker clusters can also be automatically installed on bare metal or commodity hardware without Kubernetes.
OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.
Development of a Java application Rudi: SOAP, REST, containers, database.
Technologies: Kubernetes (K3s, RKE2, Minikube, Harbor, Gitea, Jenkins, Longhorn, Keycloak, Rancher), OpenStack (Nova, Neutron, Keystone, Swift, Ceph, Cinder, Sahara, Magnum, Kayobe, Kolla, Bigrost, Ironic), Hadoop (HDFS, Ambari, Solr, Livy, Ranger, YARN, Tez, HBase, Kafka, Hive, Zookeeper, MapReduce, Spark, Oozie, Flink), virtualization (Kubernetes (K3s), VMware, Oracle), scripting (Ansible, Puppet, Juju, Shell, Groovy, Gradle, Maven).
Ritika Solanki
Last position:
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Global marketing analytics for Hitachi Energy as part of a global data modernization initiative aiming to enhance data retention, historical data availability and provide Eloqua's 2-year retention for remote interaction reporting and analytics.
Analyzed Eloqua's default retention policy and identified risk of data loss for records older than two years.
Designed and implemented historical data preservation strategy by creating transformed tables in the target data platform to archive older data while ensuring data quality dashboards.
Collaborated with the Power BI team to re-point dashboards from raw Eloqua imports to the newly created archival layer.
Leveraged Jira to track and manage data engineering tasks, bugs, and feature requests across Agile sprints; coordinated backlog prioritization and task assignment to align data pipeline development with business needs.
Power BI dashboard optimization:
Worked closely with business stakeholders to assess and understand reporting needs for reverse customer data.
Designed and implemented incremental refresh in Power BI to ensure daily updates without full data reloads.
Collaborated with Azure data engineers to optimize data processing and publication pipelines.
Stakeholder communication & data modeling:
Acted as liaison between Group Data Office and Technology Office to align data modelling standards.
Gathered requirements from data engineering team and participated in weekly status meetings to provide implementation updates and resolve blockers across teams in Germany, Poland, and India.
Documentation & quality assurance:
Prepared end-to-end technical design documentation, data flow diagrams, and Power BI audit guides for future reference.
Participated in UAT sessions with business users to validate data outputs and report accuracy.
Jörg-Ulrich Hammerbacher
Last position:
Data flows for health insurance providers
- Further development and creation of data flows for health insurance providers
- Data management across various storage systems (DB2, MSSQL, PostgreSQL, S3, custom APIs, ...)
- Documentation and training
- Planning and deployment of NiFi 2.x (major upgrade)
- Integrating Grafana for visualization, monitoring, and alerting
- Extensive use of the NiFi API to continuously monitor the system and its components
Discover over 15,000 top freelancers
Statistics of experts using Apache NiFi
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
1.5 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
94%
Master's degree or higher
59%
Certifications per freelancer
5
Most common languages
German, English, Spanish
Speak two or more languages
100%
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 NiFi
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
Data flows
Apache NiFi is used to move, route, transform, and track data between systems. It fits ingestion, ETL-style pipelines, file transfer, and event-driven integration where traceability matters.
- Source-to-target data flows
- Routing and filtering
- Format conversion and enrichment
- Provenance-aware delivery
Core skills
Strong professionals work with processors, controller services, parameter contexts, and process groups. They understand back pressure, failure handling, scheduling, and how to design flows that stay readable under change.
- Flow design and refactoring
- Secure connections and secrets handling
- Data formats such as JSON, XML, CSV, and Avro
- Operational tuning and troubleshooting
Ecosystem
NiFi often sits beside Kafka, databases, object storage, SFTP endpoints, and REST APIs. In Germany, it is common in regulated or integration-heavy environments where teams need clear lineage and controlled data movement.
When to bring help
Companies usually look for freelance expertise when flows become hard to maintain, when a migration is due, or when delivery failures need fast root-cause analysis. It also helps when a team needs someone to standardize patterns across many pipelines.
- Production incidents
- Legacy flow cleanup
- Integration redesign
- Security and access review
What good work looks like
A strong Apache NiFi specialist keeps flows modular, named clearly, and easy to operate. They document dependencies, avoid hidden logic, and build for restartability, auditability, and safe retries.
Typical deliverables
Projects often include new ingestion flows, API and file integrations, migration from scripts or hand-built jobs, and operational handover notes. The best results are flows that are simple to run, simple to trace, and simple to extend.
Frequently asked questions
Need clarity? These are the questions we hear most often about Apache NiFi.
Apache NiFi is used to move data between systems with control and visibility. Teams use it for ingestion, routing, transformation, and delivery to databases, APIs, queues, and file stores. It is a good fit when the path of the data matters as much as the data itself.
NiFi focuses on flow-based data movement, visual control, and built-in provenance. Kafka is stronger as a messaging backbone, while classic ETL tools often focus more on batch transformation and warehouse loading. Many teams use NiFi to orchestrate or complement those systems rather than replace them.
A strong Apache NiFi professional usually knows REST APIs, file and object storage, SQL, and common data formats such as JSON, XML, CSV, and Avro. Security, Linux, networking, and troubleshooting skills also matter because many issues sit at the integration layer. If Kafka, SFTP, or cloud services are in scope, those should be part of the profile too.
A simple flow can be handled by a general integration specialist with solid NiFi knowledge. Complex environments need someone who can design reusable patterns, handle failure cases, and support operations after release. If the system is business-critical, look for proven work with production Apache NiFi setups.
Most NiFi work can be done remotely because the main tasks are flow design, review, and troubleshooting. On-site time can help when access to internal systems, security reviews, or stakeholder workshops are needed. For teams in Germany, a mix of remote delivery and local workshops is often practical.
Look for clear flow design, good naming, and a calm approach to failure handling. A strong Apache NiFi specialist can explain why each processor is there, how retries work, and how data lineage is preserved. Good signs also include clean documentation and a handover that your team can operate without guesswork.
NiFi fits data ingestion, system integration, log routing, secure file exchange, and controlled API bridging. It is especially useful when teams need traceability, repeatable processing, and a visual way to manage many connected systems. It is less about heavy analytics and more about dependable movement and shaping of data.
Prepare the source systems, target systems, data formats, access rules, and any security constraints. A strong Apache NiFi expert can move faster when they know the expected volume, failure rules, and operational handover needs. It also helps to share existing flows, naming standards, and any integration pain points upfront.
The average hourly rate of freelancers in Germany who have used Apache NiFi in their recent projects is 109 €, which corresponds to a daily rate of about 872 € based on an 8-hour working day.
Of the freelancers in Germany who have used Apache NiFi in their recent projects, 94% hold at least a Bachelor's degree and 59% hold at least a Master's degree.
On average, freelancers in Germany who have used Apache NiFi in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 1.5 years.
The most common languages among freelancers in Germany who have used Apache NiFi in their recent projects are German (100%), English (100%), and Spanish (28%).
The most common industries among freelancers in Germany who have used Apache NiFi in their recent projects are Information Technology (100%), Automotive (61%), and Banking and Finance (56%).
The most common business areas among freelancers in Germany who have used Apache NiFi in their recent projects are Information Technology (100%), Business Intelligence (94%), and Product Development (78%).
Main locations of FRATCH Experts, who have recently used Apache NiFi
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
