Apache Spark Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Apache Spark
Jens Henneberg
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilizing an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Thorsten Huber
Last position:
Product Owner, AI Manager at crazyALEX.de GmbH
Digitizing real-world places with 3D/LiDAR scans to make spatial data usable for AI applications and to derive concrete use cases and prototypes from it.
- Digital capture of real-world places as a basis for faster planning and analysis
- Browser-based access to 3D data for easier use and coordination
- Turning spatial data into concrete use cases, prototypes, and AI training scenarios
- Planning basis for urban development and other digital future applications
Keywords: LiDAR, 3D scan, AI, use cases, AI training, prototyping, Python, web development, data models, architecture
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.
Marco Paffenholz
Last position:
Change management, sales development for selected financial services at Sozialbank, Bank für Sozialwirtschaft, Grey Solutions GmbH
- Development and operational implementation of effective pre-sales activities for new customer acquisition
- Operational development and implementation of best-practice conversation strategies
- Process development and process optimization
- KPI measurement, regular communication
- Coaching of the sales employees and managers involved
- On-the-job telephone training with "demonstrating" in customer conversations
- On-the-job sales coaching for sales with "demonstrating" in customer conversations
- Change management of pre-sales activities
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.
Tamás Eppel
Last position:
Senior Software Developer / Tech Lead at NDA (defense / OSINT)
- Designing the audit logging framework
- Implementing APIs for developers to integrate in their codebase
- Implementing ingestion pipeline, database query layer and UI for browsing the audit events
- Improving stability and reliability of the backend system
Philipp Grunert
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Prasad Tilloo
Last position:
Solution Architect / Senior Manager – DTC E-Commerce Platform at BRITA
- Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
- Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
- Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
- Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
- Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
- Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
- Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka
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
Danny-Michael Busch
Last position:
Senior AI Engineer at Just Add AI GmbH
- Automatic detection of content on various documents
- Recommendation Engine
- Dynamic Pricing
Lino Giefer
Last position:
Senior Data Scientist at VinFast Germany GmbH
- Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
- Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
- Automated extraction and training processes with CI/CD
- Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
- Developed and optimized embedded software for automotive control units
- Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
- Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
- Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
- Developed and trained machine learning models using PyTorch
- Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
- Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
- Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
- Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
- Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)
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
Thomas Hoefkens
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
- Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
- Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
- Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
- Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
- Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
- Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integration of RESTHeart to create a REST API for MongoDB.
- Build an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).
Steffen Seitz
Last position:
Senior Technical PM, CRM Core Experience & AI at Propstack GmbH (Scout24 S.E.)
- Built a JTBD-based prioritization framework for 3,000+ accumulated feature requests, identified 27 broker jobs, validated 8 through 25 user interviews, and used the resulting job map as a live prioritization filter for all incoming channels (Upvoty, CSAT, consulting tickets).
- Responsible for the Scout24 Lighthouse initiative: Document Intelligence with full RAG architecture (semantic chunking, bge-m3 embeddings, pgvector, BM25+Dense hybrid retrieval).
- Reduced lead time of customer feature requests to 3.1 days through code analysis, ticket specification, and independent implementation using a coding agent (Codex).
- Developed an LLM-based support agent (GPT-4o mini, Codex-generated merge requests) that reduced 3rd-level escalations from 40% to 5% of all monthly tickets.
- Integrated six partners through technical coordination, specification, backlog and release management, and led seven full stack developers.
- Eliminated regulatory exposure for brokers in six weeks through risk analysis (BGH ruling on distance selling/GDPR), new audit features, and coordination with legal and data protection officers.
Safey Haroun
Last position:
Co-Founder/Managing Partner & Chief Architect at Prinkipia GmbH
- Co-founded Prinkipia and led the growth of the team
- Defined and developed the company’s strategic direction
- Provided leadership to engineering teams across projects as chief software architect
- Drove technical vision and decision-making to ensure high-quality engineering outcomes
- Built the company culture and laid the foundation for engineering principles and best practices
- Led engineering leadership and software architecture of Prinkipia's flagship Agentic AI product
Discover over 15,000 top freelancers
Statistics of experts using Apache Spark
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
2.7 years
Positions per freelancer
11
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
96%
Master's degree or higher
73%
Doctorate
11%
Certifications per freelancer
4
Most common languages
German, English, French
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 Spark
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
Spark at scale
Apache Spark is used to process large data sets fast, across clusters and cloud platforms. Companies bring it in for batch pipelines, streaming jobs, and analytics workloads that must handle more data than a single machine can manage.
Typical deliverables
- ETL and ELT pipelines for raw, cleaned, and curated data
- Streaming jobs for event data, logs, or sensor feeds
- Spark SQL logic for reporting and ad hoc analysis
- Notebook work for prototyping, validation, and data exploration
Ecosystem fit
A strong Spark specialist knows the surrounding stack, not just the core API. That often includes Scala, Python, SQL, Delta Lake, Databricks, Hadoop, Kafka, and cloud storage such as S3 or ADLS.
When companies need help
Teams usually look for freelance Spark expertise when pipelines are slow, unstable, or costly to run. They also need help during migrations from Hadoop or Hive, when streaming breaks, or when a proof of concept must become production code quickly.
What strong experts do
Good Spark professionals write clear transformations, choose the right partitioning strategy, and avoid memory and shuffle problems. They test data logic carefully, document assumptions, and keep jobs observable so failures are easy to trace.
Germany teams
In Germany, Spark work is common in manufacturing, finance, logistics, retail, and mobility data teams. Many projects run remotely, but some companies want workshop days on-site in Germany for data access reviews, security checks, or close work with local stakeholders.
Frequently asked questions
Everything clients usually want to know about Apache Spark, in one place.
Apache Spark is used for distributed data processing when teams need fast batch work, streaming, or interactive analytics. It is a common choice for ETL pipelines, machine learning feature preparation, and large-scale SQL workloads. Companies hire Spark specialists when data volume, speed, or reliability outgrows simpler tools.
Apache Spark is often chosen over Hadoop MapReduce because it is faster and more flexible for iterative data work. Compared with Flink, Spark is usually a strong fit for mixed batch and streaming projects, while Flink is often preferred for very low-latency stream processing. The right choice depends on workload shape, data freshness needs, and team skills.
A strong Apache Spark specialist usually knows Python, Scala, and SQL well. They should also understand data modeling, distributed systems basics, cloud storage, and tools such as Delta Lake, Kafka, or Databricks when those are part of the stack. Clean testing and monitoring habits matter just as much as API knowledge.
For a small proof of concept, one experienced Apache Spark professional may be enough. Production pipelines need deeper experience with performance tuning, failure handling, and data quality checks. If the work touches streaming, governance, or migration from an older stack, senior hands-on practice becomes important quickly.
Yes, most Apache Spark work can be done remotely if access to data, repositories, and cluster environments is set up properly. For teams in Germany, on-site time is sometimes useful for kickoff workshops, security reviews, or alignment with data owners. Many projects use a hybrid setup with remote delivery and a few in-person sessions.
A good Apache Spark expert can explain why a pipeline is designed a certain way, not just what code was written. Look for clear choices around partitioning, join strategy, schema handling, and error recovery. Strong professionals also ask about input data quality, runtime limits, and how results will be monitored after release.
If Apache Spark jobs are slow, fail under load, or cost too much to run, outside help can make a difference. Another sign is when the team needs to move from notebooks to reliable production pipelines. Repeated data mismatches, streaming lag, or unclear ownership are also strong signals.
Apache Spark is used by both technical analysts and deeper data specialists, depending on the environment. Analysts often work with Spark SQL or notebooks, while more advanced work involves pipeline design, streaming, and cluster tuning. The best projects pair business context with someone who understands distributed processing well.
The average hourly rate of freelancers in Germany who have used Apache Spark in their recent projects is 98 €, which corresponds to a daily rate of about 781 € based on an 8-hour working day.
Of the freelancers in Germany who have used Apache Spark in their recent projects, 96% hold at least a Bachelor's degree, 73% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Germany who have used Apache Spark in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Germany who have used Apache Spark in their recent projects are German (99%), English (96%), and French (19%).
The most common industries among freelancers in Germany who have used Apache Spark in their recent projects are Information Technology (87%), Banking and Finance (50%), and Automotive (47%).
The most common business areas among freelancers in Germany who have used Apache Spark in their recent projects are Information Technology (98%), Product Development (81%), and Business Intelligence (77%).
Main locations of FRATCH Experts, who have recently used Apache Spark
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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