Data Lake Experts in Austria
matched in minutes by AIHire experts who design scalable lake architectures, implement ingestion with Apache Kafka and Apache Spark, and connect cloud storage with analytics and governance workflows. FRATCH matches you precisely with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Austria, who have recently used Data Lake
Alexander P.
Last position:
Owner & Lecturer at Own company for AI governance and data products, Vienna
- Consulting and interim management at the interface between IT operations and regulation
- Impact analysis 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
- Lectures in Data & Information Management and Human-Machine Interaction at University of Applied Sciences Burgenland, since 2023
- Supervision of master’s theses and participation in the examination board
- Presentations for business 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
- MLOps and AIOps in live operations
- Own applications under own brand: shared codebase, separate delivery for each target device
- AI-assisted software development (vibe coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- 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
Mario T.
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
Zeev T.
Last position:
Enterprise Architect at Coveris Group
- Built Enterprise Architecture practice covering business, application, data, and integration layers
- Created a multi-year Integration Strategy, delivering annual cost savings of several hundred thousand euros
- Defined portfolio simplification roadmap, identifying redundant systems and cost reduction opportunities
- Designed target-state enterprise architecture around D365 FSCM, enabling a best-of-breed future landscape
- Developed Master Data Management (MDM) strategy and roadmap to improve data quality and operational efficiency
- Provided enterprise-wide architectural direction ensuring alignment and eliminating redundant initiatives
- Established reusable architecture patterns adopted by delivery teams
- Facilitated cross-functional architecture forums to align product and delivery teams
- Translated enterprise architecture guidance into practical delivery decisions
- Drove practical adoption of architecture guidance across initiatives rather than acting as a gatekeeper
- Identified redundant systems enabling substantial cost reduction potential
- Enabled cost transparency in integration landscape
- Enabled fact-based investment prioritization decisions
Benjamin A.
Last position:
Multi-Project Manager at Trading Company
- Setup of a new Data Warehouse (Budget ~€15M 2025 – 2026)
- Backend modernization project (Budget ~€5M 2025 – 2026)
- Standard software rollout with custom programming (Budget ~€9M 2025 – 2026)
Gerald G.
Last position:
Data Design Authority at Department of Government Enablement
- Responsible for realigning the data architecture of the Abu Dhabi government to achieve a fully AI-driven public administration
- Definition of modeling standards
- Creation of a conceptual and logical model for the entire Abu Dhabi government administration
- Definition of data quality and data security standards
Kurt B.
Last position:
Backend / Microservice Developer, DevOps, Test Automation at RCA, Rail Cargo Austria AG
- Backend / Microservice Developer, DevOps, Test Automation
- ~100 Devs, ~10 Teams, per team: 1 PO, 1 Scrum Master, 1 UX, 1 Developer, 1 Tester
- .net core 8, 9, C#
- Microservices, Clean-Architecture, MediatR, CQRS
- GraphQL, REST, SDL
- Azure DevOps, CI / CD-pipelines, Azure-Service Bus, Rabbit-MQ, Kafka, Azure App Configuration, Azure KeyVault, Azure Kubernetes AKS
- Splunk, dashboards, custom metrics, Elastic-Search, Kibana (ELK)
- Azure SQL-Databases, Azure Cosmos DB
- Architecture decisions, event governance, COP (Backend, DevOps, FrontEnt, Test Automations)
- AI, Copilot, creating test templates
- Scheduler, Hangfire, Quartz
- Automated unit and integration tests
- Automated E2E tests, Playwright test automation, BDD, Gherkin, Cucumber
- Tracking of shipments
- GIS, GPS data, geofence, geo search, position tracking, asset positions
- Jira, Confluence
- Focus on high-performance message-oriented architecture (~xx million messages per month per service)
- Structured logging, Serilog, OTel, Splunk, Application Monitoring
- Integration of different position data sources (GPS-based data) into Azure Data Lake
Rene S.
Last position:
Head of Digital Services & IT at reet systems gmbh / THEOPHIL Holding GmbH
- Overall responsibility for IT, software development, and digital services of the company for brands such as Rosenberger, Rosehill, Burger King Austria (approx. 70 companies)
- Built the holding's lakehouse and data analytics platform
- Established and led the software development and IT department
- Established and led the operation (cloud-native AWS) of the B2B platform
- Connected IoT systems and developed models for predictive maintenance and production planning, data lake/lakehouse, and BI
- Preparation for ISO 27001 information security certification
- Technologies: Cloud, AWS, Java, Cypress, Angular, Python, Go
Bernhard K.
Last position:
AI Consultant at Bitpanda
- Advising on AI strategy and implementation for one of Europe's leading digital asset platforms
- Helping teams integrate agentic AI workflows, optimize developer productivity through AI-assisted tooling, and evaluate emerging AI technologies for fintech applications
Manfred S.
Last position:
Data Solutions Consultant at ONECEPT GmbH
- As a Data Engineer and Cloud Architect, I am implementing various use cases for our customers.
- From a technical point of view, the focus is on data integration projects in Azure, specializing in data and Delta Lakes using the Apache Framework or Azure products like Synapse Analytics or Fabric.
Peter K.
Last position:
Sabbatical
Gasper Z.
Last position:
Senior BI Consultant at PMONE GmbH
Discover over 15,000 top freelancers
Statistics of experts using Data Lake
Aggregated from the professional profiles of matched freelancers.
Experience
23 years
Position duration
2.2 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
89%
Master's degree or higher
67%
Certifications per freelancer
3
Most common languages
German, English, French
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 Austria 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 Austria using Data Lake
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.
Data Lake 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 (92%)
- Banking and Finance (75%)
- Education (58%)
- Manufacturing (50%)
- Retail (42%)
- Automotive (33%)
- Professional Services (33%)
- Telecommunication (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a Data Lake provides
A Data Lake is a central storage environment for structured, semi-structured and unstructured data in its original form. It commonly uses cloud object storage or distributed file systems, allowing teams to retain raw events, documents, logs, media and business records for later processing. Unlike a rigid warehouse model, its structure can be applied when the data is read.
Common project uses
Companies use data lakes as foundations for analytics, machine learning and operational reporting. Typical deliveries include:
- Ingesting application events, IoT signals and business data
- Creating zones for raw, prepared and curated datasets
- Supporting feature engineering and model training
- Feeding dashboards, warehouses and downstream services
- Preserving historical data for audits and exploration
Ecosystem and tooling
Strong work with a Data Lake spans storage, processing, orchestration and access control. Common technologies include Amazon S3, Azure Data Lake Storage, Google Cloud Storage, Databricks, Apache Spark, Apache Kafka, Apache Iceberg, Delta Lake, Trino and dbt. Specialists also work with Airflow or cloud-native workflow services to schedule pipelines and monitor dependencies.
When expertise matters
Freelance expertise is useful when a company is replacing fragmented file stores, scaling beyond a warehouse, or making new data sources usable. It also helps during cloud migration, lakehouse adoption and remediation of unreliable pipelines. In Austria, teams may need professionals who can collaborate remotely across locations while documenting decisions clearly for local stakeholders.
Skills that protect value
A reliable Data Lake is more than a large storage bucket. Professionals define ownership, naming, metadata, retention, lineage and access policies before uncontrolled growth creates risk. They set up validation, schema evolution, encryption, observability and recovery procedures, while keeping compute costs and query performance visible. Knowledge of SQL, Python, cloud security and data modeling is often valuable alongside platform expertise.
How to assess professionals
Look for specialists who can explain trade-offs between a lake, warehouse and lakehouse in business terms. Strong candidates show how they handled late-arriving data, duplicate records, changing schemas and failed pipeline runs. Ask for a clear delivery plan covering ingestion, quality checks, cataloging, permissions and handover. The best professionals test assumptions with real data and leave maintainable workflows, useful documentation and practical operating guidance.
Frequently asked questions
Everything clients usually want to know about Data Lake, in one place.
A Data Lake stores data from many sources in a flexible format for analytics, machine learning, reporting and exploration. It can hold events, files, logs, sensor readings and transactional extracts before teams decide how to structure them.
A Data Lake usually keeps raw data and applies structure later, while a warehouse organizes modeled data before analysis. Lakes support broader data types and exploratory work; warehouses often provide simpler, more predictable reporting for governed business queries.
A Data Lake focuses on flexible storage and processing, whereas a lakehouse adds warehouse-like controls such as transactions, table management and stronger governance on the same underlying storage. The right choice depends on query needs, data quality, team skills and existing cloud services.
A strong Data Lake specialist often brings skills in SQL, Python, cloud storage, distributed processing and pipeline orchestration. Experience with Apache Spark, Apache Kafka, Databricks, catalogs, identity management and data quality checks is also useful.
The right Data Lake experience depends on the project scope, source systems and compliance requirements rather than a fixed duration. A small ingestion workflow may need one focused specialist, while a multi-domain platform calls for expertise in architecture, governance, security and operations.
Yes, Data Lake work is often suitable for remote collaboration because cloud environments, repositories and documentation can be shared securely. On-site sessions may still help with source-system discovery, stakeholder workshops or access reviews, especially when teams work across Austrian locations.
Evaluate whether the Data Lake design covers ownership, metadata, lineage, permissions, validation, monitoring and recovery. Ask the specialist to explain how the solution handles schema changes, duplicate data, failed loads and future growth, not just how files reach storage.
Before starting, a Data Lake professional should clarify source systems, data volumes, freshness needs, consumers, cloud constraints and security responsibilities. They should also confirm who owns data definitions, which tools are approved and what handover or operating documentation the company expects.
The average hourly rate of freelancers in Austria who have used Data Lake in their recent projects is 110 €, which corresponds to a daily rate of about 876 € based on an 8-hour working day.
Of the freelancers in Austria who have used Data Lake in their recent projects, 89% hold at least a Bachelor's degree and 67% hold at least a Master's degree.
On average, freelancers in Austria who have used Data Lake in their recent projects have 23 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Austria who have used Data Lake in their recent projects are German (100%), English (100%), and French (33%).
The most common industries among freelancers in Austria who have used Data Lake in their recent projects are Information Technology (92%), Banking and Finance (75%), and Education (58%).
The most common business areas among freelancers in Austria who have used Data Lake in their recent projects are Information Technology (100%), Business Intelligence (83%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Data Lake
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
