Apache Spark Experts in Austria
for scalable data processing, matched in minutes with vetted and available professionalsHire experts who process large datasets, build reliable ETL pipelines and develop machine learning workflows with Apache Spark, PySpark and Spark SQL. Get a precise match with vetted, available freelancers who fit your project and can work remotely or with your Austrian team.
Meet FRATCH Experts in Austria, who have recently used Apache Spark
Alexander P.
Last position:
Owner & Lecturer at Artellico / Own company for AI governance and data products
- Consulting and interim management at the intersection of IT operations and regulation
- Impact assessment and implementation planning for NISG 2026 and the EU AI Act, including risk management and reporting and evidence processes
- Training for governing bodies and employees on regulatory obligations
- Teaching assignments in Data & Information Management and Human-Machine Interaction at Hochschule Burgenland, since 2023
- Supervision of Master's theses and participation on examination boards
- Industry talks for businesses and educational institutions
- Design and development of data and AI products, platforms and pipelines
- Privacy-first architectures and Zero-Knowledge encryption, cloud-native on EU infrastructure
- Integration with bank account systems using SEPA direct debit mandates and message formats under ISO 20022 (pain.008, camt.053)
- MLOps and AIOps in live operations
- Own applications under my own brand: shared codebase, separate deployment for each target device
- AI-assisted software development (vibe-coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Professional publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- Professional publications on data sovereignty, cloud economics and industrial image processing
- AI governance / compliance: data quality, Responsible AI, EU AI Act readiness, risk classification, AI ethics
Karl F.
Last position:
Managing Director at ONECEPT GmbH
Christian E.
Last position:
Cyber Trust Austria Silver Certification at PrimeFaktor GmbH
Cyber Trust Austria Silver Certification
- Led application and implementation of the Cyber Trust Austria Silver label (KSV1870 Cyber Risk A-Rating; 25 validated controls)
- Mapped and fulfilled requirements covering risk management, incident response, access control, vulnerability and penetration testing, BCM, and supply-chain security, aligned with ISO/IEC 27001/27002 control themes and NIS 2 / NISG 2026 expectations
- Coordinated stakeholders, compiled audit evidence, and completed KSV1870 validation
Manuel P.
Last position:
AI Engineer at Misumi Europe GmbH & Motius GmbH
- Designed and built a next-generation NLP platform to accelerate sales-driven customer service through intelligent request analysis and routing, reducing average customer query response time by 30%.
- Architected a hybrid NLP system combining Large Language Models (LLMs) with traditional NLP pipelines for robust, explainable results.
- Developed request classification and routing mechanisms to accelerate customer support teams in handling customer queries faster and more accurately.
- Optimized LLM based data extraction and classification with context engineering.
- Integrated the platform into customer service processes, reducing response times and enhancing workforce efficiency.
Stefan D.
Last position:
BI Consultant in Controlling at Reutter GmbH
- Extraction, transformation, and cleansing of data from Microsoft Dynamics AX
- Creation of sales reports in Power BI
- Training employees in business intelligence
- Technologies: Power BI, SQL, SQL Server Integration Services (SSIS)
Stefania D.
Last position:
Data Engineer at Storebox
Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI
Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine
- Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
- Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
- Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
- Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
- Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
- Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
- Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).
Marcel S.
Last position:
Senior AI Engineer - Python at Insurance Company
Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock
Achievements:
- Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
- Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
- Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
- Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.
Fabio G.
Last position:
IT Architect, Requirements Analyst and Consultant at CANCOM
- Supports CANCOM customers in migrating legacy on-prem systems to Microsoft Fabric and Microsoft Foundry
- Takes over and stabilizes existing solutions after a short handover
- Business analysis and requirements engineering for migration to a new cloud environment
- Optimization of machine learning models for feature extraction and customer profiling
- Ensures data protection and compliance
- Leads the migration of on-prem systems to Microsoft Fabric
- Designs new AI platforms for clients
- Tests the integration of chatbots for document intelligence with Microsoft Foundry, including requirements analysis, implementation, validation, and client communication
Mario T.
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
Hossein A.
Last position:
Datawarehouse Consultant at LENZING AG
- Consulting on the enterprise data-warehouse and reporting practice at one of Austria's largest industrial groups.
- Designing and standardizing Power BI dashboards and data-visualization governance for company-wide enterprise reporting.
- Developing a WCAG-compliant, colorblind-safe visualization standard (Okabe-Ito palette) to harmonize dashboards across the organization.
Gasper Z.
Last position:
Senior BI Consultant at PMONE GmbH
Discover over 15,000 top freelancers
Statistics of experts using Apache Spark
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
2 years
Positions per freelancer
12
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Manufacturing, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100%
Master's degree or higher
90%
Doctorate
20%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Austria 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 29 Oct 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 (73%)
- Manufacturing (64%)
- Banking and Finance (55%)
- Professional Services (55%)
- Education (45%)
- Retail (45%)
- Healthcare (36%)
- Transportation (36%)
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. It supports batch workloads, streaming, SQL analytics and machine learning through a unified framework. Teams use it when data volumes, processing speed or pipeline complexity exceed what a single machine can handle.
Data workloads
Apache Spark specialists build the data layer behind analytical and operational systems. Common deliverables include:
- Batch ETL and ELT pipelines for data warehouses and data lakes
- Streaming applications for events, logs and real-time decisions
- Spark SQL models for reporting and interactive analysis
- Feature pipelines and machine learning workflows with MLlib
Core ecosystem
Strong Apache Spark expertise includes more than writing transformations. Professionals work with PySpark, Scala or Java, DataFrames, RDDs and Spark SQL, while selecting suitable partitioning, joins and storage formats. They often connect Spark with Hadoop, Hive, Kafka, Delta Lake, Parquet, cloud object storage and orchestration tools such as Airflow.
When to bring in specialists
Companies usually need freelance expertise when a data platform is slow, unstable or difficult to scale. A specialist can assess cluster configuration, redesign inefficient jobs, migrate legacy Hadoop workloads or establish standards for testing and deployment. In Austria, this can support manufacturers, financial services, retail and research teams while keeping collaboration remote, on-site or hybrid.
Delivery and reliability
A capable professional makes data processing observable and repeatable. They define schemas, manage dependencies, handle late or corrupt data and protect pipelines from duplicate processing. They also use Spark UI, logs and metrics to find shuffle-heavy stages, memory pressure and skewed partitions before these issues affect downstream users.
Choosing the right expert
Look for evidence of production workloads similar to yours, not only familiarity with the API. Ask how the specialist approaches data quality, cost control, security, deployment and recovery. Experience with your storage layer, cloud environment and language expectations matters, especially when Austrian stakeholders need clear documentation and close collaboration.
Frequently asked questions
Need clarity? These are the questions we hear most often about Apache Spark.
Apache Spark is used to transform, analyze and move large datasets across distributed computing clusters. Companies use it for batch ETL, data lake processing, streaming analytics, SQL reporting and machine learning pipelines.
Apache Spark offers a broad unified environment for batch processing, SQL, streaming and machine learning. Hadoop MapReduce can suit established batch systems, while Apache Flink is often considered for stream-first workloads that require event-time processing and low latency.
A strong Apache Spark specialist usually understands Python, Scala or Java, SQL, data modelling and distributed systems. Experience with Kafka, Airflow, cloud storage, Kubernetes, Delta Lake, Parquet and a warehouse or lakehouse architecture is also valuable.
The required Apache Spark experience depends on the workload, data volume and operational risk. A focused pipeline improvement may need a specialist who can diagnose a defined issue, while a new lakehouse or streaming platform calls for broader architecture, security and deployment experience.
Yes, Apache Spark projects can often be delivered remotely when repositories, environments and data access are well managed. Austrian teams should agree on documentation, meeting cadence, data residency requirements and whether occasional on-site workshops or German-language communication are needed.
Apache Spark may be excessive for small datasets, simple transformations or workloads that need only a lightweight database query. A specialist should compare it with SQL engines, warehouse-native processing or stream-focused tools instead of introducing a cluster without a clear scaling or integration need.
Ask an Apache Spark freelancer to explain a production pipeline they optimized, including partitioning, joins, failure handling and monitoring. Review their reasoning with a representative data task and check whether they can communicate trade-offs clearly to both technical and business stakeholders.
Reliable Apache Spark pipelines have explicit schemas, repeatable deployments, tested transformations and clear data-quality checks. They also address idempotency, checkpointing, access control, observability and recovery so that a failed job does not silently corrupt downstream data.
The average hourly rate of freelancers in Austria who have used Apache Spark in their recent projects is 105 €, which corresponds to a daily rate of about 841 € based on an 8-hour working day.
Of the freelancers in Austria who have used Apache Spark in their recent projects, 100% hold at least a Bachelor's degree, 90% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Austria who have used Apache Spark in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Austria who have used Apache Spark in their recent projects are German (100%), English (100%), and French (36%).
The most common industries among freelancers in Austria who have used Apache Spark in their recent projects are Information Technology (73%), Manufacturing (64%), and Banking and Finance (55%).
The most common business areas among freelancers in Austria who have used Apache Spark in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (73%).
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.
Vienna Graz 
Vienna Countries:
- Germany
- Austria
- Switzerland
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