Apache Spark Experts in Nuremberg
matched in minutes by AIHire experts who process large datasets, build reliable ETL pipelines and optimize Spark SQL workloads across cloud and on-premise environments. FRATCH connects you with vetted, available freelancers through precise, fast matching.
Meet FRATCH Experts in Nuremberg, who have recently used Apache Spark
Arun Sai T.
Last position:
AI-Backend Developer Intern at Calvergy UA
- Integrated complex AI-based energy system models into the frontend framework, enabling the visualization of insights for 6+ key clients and maximizing energy utilization.
- Maximized energy efficiency and utilization by architecting the seamless data flow between AI models and the user interface for rapid, actionable reporting.
Pawan S.
Last position:
CAPTCHA Recognition using CRNN
- Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
- Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
- Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
- Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
- Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib
Uddipan B.
Last position:
Research Team Member at Munich Music Labs, TUM
- Focused on exploring the intersection of Music and AI.
Vasuraj B.
Last position:
Cloud Data Analyst at Bhatia Reply
- Analyzed 50K+ customer records using SQL and Python in a cloud services firm, identifying trends
- Designed interactive Tableau dashboards for sales and marketing stakeholders, reducing report
- Developed ARIMA and AutoARIMA time series models to forecast AWS resource utilization, cutting
- Automated ETL pipelines with Python, improving workflow efficiency by 20% for scalable data
- Collaborated with DevOps teams to deploy 3 machine learning models in production using Docker
Ioan D.
Last position:
Senior Software Developer at ING
- Tribe Home, Product Area 4 - Customer in Life, Squad Cybertron.
- Analysis, design, development, and testing of new requirements for Optimmo, mortgage financing software.
- Analysis, design, development, and testing of the JEE application MWS kredit-baufi.
- Analysis, design, development, and testing of the Wicket Optimmo application.
- Analysis, design, development, and testing of kredit-baufi batch programs.
- Migration of kredit-baufi batches to RHEL9.
- CiL SCS consumer pacts with Finagle.
- CiL SCS touch point architecture integration.
- Team size: 10.
- Tools / Frameworks: OpenJDK Java 17, Kotlin 1.6.0, Azure, Jenkins, Stash, JEE, GitLab, JIRA, Confluence, git, Spring 6.0, Spring Cloud, Spring Data, Hibernate, JPA, JMS, Kafka, Oracle, PL/SQL, Red Hat Enterprise Linux (RHEL), Maven, REST, JBoss, IntelliJ IDEA, Wicket 9 and 10, Istio.
Ekaansh K.
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Guino N.
Last position:
Senior Data Engineer at Infomotion
- Built a data analytics platform for Karl Storz
- Developed all ETL processes in a generic way
- Prepared and supplied data in Databricks Delta tables for use in Databricks Machine Learning
- Technologies & Tools: Azure Data Factory, CI/CD pipeline with GitHub DevOps, Python, Azure Databricks (Unity Catalog), T-SQL
Andreas V.
Last position:
Senior Software Developer, Architect at ifm Solutions GmbH
- IoT platform to connect, transform and get actionable results
- Built a microservice observability solution to enhance developer and operations insights
- Did advanced performance optimizations in .NET code, DB and time series
- Provided architectural consultation for developer teams on performance, scalability, reliability and code quality
- Evaluated and built PoCs for new technologies including time series DBs and messaging platforms
- Technologies: C#/F#/Rust, InfluxDB, ClickHouse, Prometheus, Grafana, k6, RabbitMQ, EMQX, Docker, Kubernetes, Azure AKS
Discover over 15,000 top freelancers
Statistics of experts using Apache Spark
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
1.6 years (Germany: 2.7 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Automotive, Banking and Finance
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
75% (Germany: 71%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Hindi
Speak two or more languages
100% (Germany: 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 Nuremberg 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 Nuremberg 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Apache Spark 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 (75%)
- Banking and Finance (63%)
- Education (50%)
- Manufacturing (50%)
- Energy (38%)
- Healthcare (38%)
- Professional Services (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Distributed data processing
Apache Spark is an open-source engine for processing large datasets across clusters. Teams use it for batch processing, streaming analytics, interactive queries and machine learning workflows. Its APIs for Scala, Python, Java and R support data products that need speed, scale and flexible deployment.
Workloads and deliverables
Spark specialists turn raw data into dependable pipelines, analytical datasets and production services. Typical assignments include:
- Building ETL and ELT pipelines for warehouses and data lakes
- Processing event streams with Structured Streaming
- Creating Spark SQL models and reusable data transformations
- Preparing features for machine learning workflows
- Migrating legacy Hadoop jobs to modern Spark applications
Ecosystem and tooling
Apache Spark commonly works with Delta Lake, Apache Iceberg, Apache Hudi, Hadoop, Hive and Kafka. Professionals also use Airflow, dbt, Kubernetes and cloud services such as Databricks, Amazon EMR, Google Cloud Dataproc and Azure Synapse. Strong Spark work includes version control, automated testing, observability and deployment practices.
When expertise matters
Companies bring in freelance Spark experts when data volumes, latency requirements or pipeline complexity exceed the capacity of an internal team. Useful signals include slow jobs, unstable streaming workloads, rising cloud costs or a migration from Hadoop. In Nuremberg, on-site collaboration can support industrial, logistics and enterprise data initiatives, while remote delivery works well with clear documentation and shared delivery routines.
Skills to assess
A capable professional understands distributed execution, partitions, shuffles, joins, caching and memory management. They can inspect query plans, tune Spark SQL, manage cluster resources and explain trade-offs between batch and streaming designs. Experience with Python or Scala, cloud storage, data governance and CI/CD is often just as important as Spark API knowledge.
Choosing a strong specialist
Review evidence of production pipelines rather than isolated notebooks. Ask how the specialist handled skewed data, failed tasks, schema changes, late events and data-quality checks. A strong engagement has measurable acceptance criteria, reproducible tests, monitoring and a handover plan. Candidates should also communicate clearly with data teams, application teams and business stakeholders.
Frequently asked questions
Quick answers to the questions that come up most around Apache Spark.
Apache Spark is used for distributed batch processing, real-time stream processing, SQL analytics and machine learning preparation. Companies use it to transform data from lakes, warehouses, databases and event systems into reliable analytical outputs.
Apache Spark provides a broad processing environment covering batch, SQL, streaming and machine learning workflows. Hadoop MapReduce is more focused on disk-based batch processing, while Apache Flink is often chosen for stateful, low-latency streaming. The right choice depends on workload patterns, existing systems and team skills.
A strong Apache Spark specialist often works with Python or Scala, SQL, Kafka, cloud object storage and lakehouse formats such as Delta Lake or Apache Iceberg. Airflow, Kubernetes, Databricks, data quality testing and CI/CD are also valuable for production delivery.
Apache Spark work requires enough practical experience to reason about partitions, shuffles, joins, memory use and failure recovery. A smaller transformation may need focused support, while a streaming platform or migration benefits from someone who has operated comparable workloads in production.
Apache Spark projects are often suitable for remote collaboration because code, data contracts, monitoring and deployment workflows can be shared digitally. Teams in Nuremberg should agree on access controls, working language, documentation standards and meeting windows before work begins; on-site sessions can help during discovery or complex handovers.
Apache Spark runs inside Databricks with managed clusters, notebooks, workspace collaboration and additional lakehouse tooling. Databricks can reduce operational work, but teams should still assess governance, portability, cost controls and the need for direct cloud or Kubernetes management.
A quality Apache Spark solution has clear data contracts, repeatable tests, sensible partitioning and monitoring for performance and data quality. Ask the specialist to explain query plans, failure handling and cost trade-offs, then review a small representative task or technical walkthrough.
An Apache Spark freelancer may deliver batch or streaming pipelines, Spark SQL transformations, performance improvements, migration plans or production runbooks. The engagement should also include tests, deployment instructions, monitoring requirements and documentation that lets the internal team operate the result.
The average hourly rate of freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects is 88 €, which corresponds to a daily rate of about 707 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects, 100% hold at least a Bachelor's degree and 75% hold at least a Master's degree.
On average, freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.6 years.
The most common languages among freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects are German (100%), English (100%), and Hindi (38%).
The most common industries among freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects are Information Technology (100%), Automotive (75%), and Banking and Finance (63%).
The most common business areas among freelancers in Nuremberg, Germany who have used Apache Spark in their recent projects are Information Technology (100%), Business Intelligence (88%), and Product Development (88%).
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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Hamburg 
Munich 
Cologne 
Frankfurt Request a free demo
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