Apache NiFi Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Apache NiFi
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management steering during a restructuring program (approx. 80 participants)
- Set up a PMO to ensure transparency, reporting and data-driven decisions
- Created an integration template to transfer team s...
Panagiotis T.
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 M.
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
Manuel S.
Last position:
Project Manager at Univention
Industry: digital sovereignty, public sector
Responsibilities:
- Project coordination (teams: consulting, development, testing, deployment/operations)
Products and standards:
- Jira, Confluence, Asana, Miro, Mural
- Open Source, Keycloak, Open Xchange, ownCloud
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
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
Lazaros K.
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)
Bianca S.
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
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).
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 S.
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Maziyar K.
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Martin M.
Last position:
Freelance Data Architect at Zeppelin
- Evaluation and scoring of various technologies as future telematics platform (Kafka Streams, Spark, Splunk, Snowflake)
- Improve test framework and scalability of Telematics streaming service (Scala, Property-Based Testing, Kafka, Kafka Streams, Kubernetes)
Alain Gérard E.
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
Discover over 15,000 top freelancers
Statistics of experts using Apache NiFi
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
1.5 years
Positions per freelancer
14
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
67%
Doctorate
6%
Certifications per freelancer
5
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Apache NiFi 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 (100%)
- Automotive (58%)
- Banking and Finance (53%)
- Manufacturing (47%)
- Retail (47%)
- Healthcare (42%)
- Insurance (42%)
- Telecommunication (42%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Dataflow foundation
Apache NiFi is an open-source platform for moving, transforming and routing data between systems. Its visual flow-based interface makes data movement easier to inspect, control and change. NiFi supports batch and streaming patterns across files, APIs, databases, message brokers and cloud services.
Core capabilities
NiFi uses processors, connections, controller services and process groups to model data flows. Each flow can apply transformation, enrichment, filtering, validation and routing rules while preserving flow history and operational context. Back pressure, prioritisation and replay controls help keep pipelines stable under changing loads.
Ecosystem and tooling
Specialists work with NiFi Registry for versioned flow management and with MiNiFi for lightweight edge deployments. Common integrations include Kafka, relational databases, object storage, REST APIs, MQTT, Elasticsearch and Apache Hadoop components. Secure deployments often involve TLS, certificate authorities, identity providers, parameter contexts and role-based access.
- Design reusable process groups and templates
- Connect APIs, databases, files and message systems
- Apply schema checks, enrichment and routing rules
- Monitor provenance, queues and processor health
Where it fits
Companies use NiFi for data ingestion, event distribution, operational synchronisation and edge-to-core collection. Typical solutions support manufacturing telemetry, logistics events, financial records, public-sector data exchange and enterprise integration. In Germany, teams may also use it across industrial and regulated environments where traceability and controlled data handling matter.
When to hire expertise
Freelance expertise helps when a flow has grown difficult to maintain, integrations must be delivered quickly or a production rollout needs stronger controls. Specialists can review an existing canvas, establish deployment practices, connect NiFi with Kafka or cloud storage and improve observability. Remote collaboration works well when access, documentation and operational ownership are clearly defined; on-site work can help with restricted environments.
- Assess throughput, queue pressure and failure handling
- Refactor large flows into maintainable process groups
- Establish deployment, backup and recovery procedures
- Document ownership, alerts and operational handover
Signs of quality
Strong professionals understand both NiFi’s visual model and the systems around it. They design for idempotency, schema evolution, security, retry behaviour and graceful recovery rather than simply connecting processors. They explain trade-offs clearly, test with realistic data and leave behind flows that another team can operate confidently.
Frequently asked questions
Need clarity? These are the questions we hear most often about Apache NiFi.
Apache NiFi is used to collect, route, transform and monitor data moving between applications, databases, files, devices and cloud services. Companies use it for ingestion pipelines, system synchronisation, event distribution and edge data collection.
Apache NiFi focuses on visual flow design, protocol integration, routing and operational control. Kafka is primarily an event streaming and durable messaging platform, while traditional ETL tools often focus on scheduled batch transformations. NiFi can complement Kafka rather than replace it.
A strong Apache NiFi specialist should understand REST and messaging protocols, SQL, data formats such as JSON and Avro, and secure authentication. Experience with Kafka, Kubernetes, cloud storage, Linux operations and observability is also valuable.
The right level depends on the flow’s scale, integrations and production risk. A simple ingestion flow may need focused configuration support, while a regulated or distributed deployment calls for a professional who has handled security, performance, versioning, recovery and operational handover.
Apache NiFi is well suited to remote collaboration when specialists receive secure access, sample payloads, architecture context and clear ownership boundaries. For German teams, English is common in technical work, while German language skills can help with workshops, compliance discussions and communication with local operations.
On-site collaboration can help when data sources sit in restricted facilities, network access is tightly controlled or several operational teams need to agree on ownership. NiFi specialists can still deliver much of the design, configuration and testing remotely when environments are accessible.
Ask for examples of flows that handled failure, replay, schema changes and security requirements, not just screenshots of a canvas. A capable Apache NiFi professional explains queue behaviour, provenance, retries, parameter management and how the team will operate the result.
Apache NiFi originated from the NiagaraFiles project and is often shortened to NiFi. The earlier name matters when searching older documentation or project histories, but current integrations, releases and community resources use Apache NiFi.
The average hourly rate of freelancers in Germany who have used Apache NiFi in their recent projects is 106 €, which corresponds to a daily rate of about 848 € 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, 67% hold at least a Master's degree, and 6% hold a doctorate.
On average, freelancers in Germany who have used Apache NiFi in their recent projects have 18 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 (26%).
The most common industries among freelancers in Germany who have used Apache NiFi in their recent projects are Information Technology (100%), Automotive (58%), and Banking and Finance (53%).
The most common business areas among freelancers in Germany who have used Apache NiFi in their recent projects are Information Technology (100%), Business Intelligence (95%), and Product Development (74%).
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
