Data Lake Experts in Austria
matched in minutes with vetted, available freelance specialistsHire experts who design governed data platforms, build reliable ingestion pipelines and prepare analytics-ready datasets across cloud and hybrid environments. FRATCH matches you quickly and 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 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
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
Kurt B.
Last position:
Backend / Microservices Developer, DevOps, Test Automation at Fa. RCA, Rail Cargo Austria AG
- Backend / Microservices Developer, DevOps, Test Automation
- ~100 Developers, ~10 Teams, per Team: 1 PO, 1 ScrumMaster, 1UX, 1 Developers, 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, FrontEnd, Test Automation)
- AI, Copilot, creating Test Templates
- Scheduler, Hangfire, Quartz
- Automated Unit and Integration Tests
- Automated E2E Tests, Playwright Test Automation, BDD, Gherkin, Cucumber
- Shipment tracking
- GIS, GPS data, geofence, geo search, position tracking, asset positions
- Jira, Confluence
- Focus on high-performance message-oriented architecture (~xx e6 messages / month / service)
- Structured logging, Serilog, OTel, Splunk, Application Monitoring
- Integration of different position data sources (GPS-based data) into AzureDataLake
Laura H.
Last position:
Sr. BI Consultant & Project Manager at Multivariata
- Project Lead, Sr. BI Expert, Data Scientist, Automation Engineer for Marketing Analytics | Customer Insights (retail, e-commerce)
- Product Manager: Asset Metadata Ingest & Provide
- Product Owner Business Intelligence – responsible for 2 teams: cloud data engineering, data warehouse (logistics)
- Product Owner for setting up a reporting platform on Azure & Power BI (finance)
Mario T.
Last position:
External Lecturer at FH Kufstein Tirol – University of Applied Sciences
- Study: Data Science & Intelligent Analytics
- Module: Big Data Processing
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
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
24 years
Position duration
2.4 years
Positions per freelancer
16
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
90%
Master's degree or higher
60%
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 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 29 Oct 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 (77%)
- Education (54%)
- Manufacturing (46%)
- Professional Services (46%)
- Retail (46%)
- Automotive (38%)
- Government and Administration (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a Data Lake is
A Data Lake stores raw and refined data in its original form, including structured records, log files, documents, images and event streams. It separates storage from processing so teams can collect large volumes before deciding how each dataset will be used. A well-designed lake supports analytics, machine learning, reporting and operational use cases without forcing every source into one rigid schema.
Core architecture
Data Lake work covers ingestion, storage, transformation, cataloguing and controlled access. Specialists select architectures that match cloud, on-premises or hybrid requirements and define zones for raw, validated and consumption-ready data. They also establish metadata, lineage, retention and recovery practices so the platform remains understandable as sources and users grow.
- Connect databases, APIs, files and event streams
- Design batch and streaming ingestion
- Organise storage with open data formats
- Add catalogues, lineage and access controls
Ecosystem and tooling
Common ecosystems include Amazon S3 with AWS Glue and Lake Formation, Azure Data Lake Storage with Data Factory and Synapse, and Google Cloud Storage with Dataproc or BigQuery. Specialists may also work with Apache Spark, Kafka, Delta Lake, Apache Iceberg, Apache Hudi, dbt, Airflow and Terraform. The right combination depends on data volume, latency, governance and existing skills.
When companies need specialists
Companies often bring in freelance expertise when a lake has become difficult to trust, expensive to operate or slow to serve. External specialists can consolidate scattered sources, modernise warehouse architecture, migrate workloads to the cloud or prepare a foundation for machine learning. In Austria, projects may involve teams across manufacturing, finance, retail, energy and public services.
- Data sources are growing without clear ownership
- Analysts cannot find or interpret trusted datasets
- Pipelines fail silently or lack observability
- Access rules and sensitive-data controls are unclear
Skills that distinguish strong professionals
Strong professionals combine data modelling with platform engineering and practical governance. They understand partitioning, file formats, schema evolution, orchestration, testing and cost control. They can explain trade-offs between a Data Lake, a warehouse and a lakehouse, then document decisions for analysts, security teams and business owners.
Collaboration and delivery
A capable specialist starts by mapping sources, users, risks and expected outcomes. Deliverables may include an architecture plan, ingestion pipelines, transformation models, catalogue setup, monitoring dashboards and operating documentation. Remote collaboration works well when ownership, access and acceptance criteria are clear; on-site work can help when source systems or stakeholders require close coordination.
Frequently asked questions
Everything clients usually want to know about Data Lake, in one place.
A Data Lake is used to collect and retain raw data from databases, applications, devices, documents and event streams. Companies use it for analytics, machine learning, exploration, reporting and other workloads that need access to varied data.
A Data Lake usually stores data before it is fully structured, while a warehouse serves curated data through defined models and query patterns. A lake offers flexibility for discovery and machine learning; a warehouse often provides more predictable performance and governance for recurring business reporting.
A lakehouse combines low-cost, flexible lake storage with warehouse-style tables, transactions and governance. It can suit organisations that want analytics and machine learning on shared data, but the choice depends on workload patterns, existing tools, skills and operational needs.
A strong Data Lake freelancer often works with cloud storage, Apache Spark, Kafka, Airflow, SQL, Python, Terraform and infrastructure security. Experience with catalogues, data quality, lineage, observability and privacy controls is equally important for production delivery.
A Data Lake project needs enough practical experience to cover architecture, ingestion, governance and operations, not just storage configuration. The right level depends on whether the work is a discovery exercise, a migration, a new platform or the stabilisation of a live environment.
Most Data Lake design, pipeline development and documentation can be delivered remotely from Austria. On-site collaboration may help when specialists must inspect legacy systems, coordinate with infrastructure teams or conduct workshops in person; clear access and communication processes remain essential.
A Data Lake specialist should explain trade-offs in plain language and show how reliability, security, lineage and cost will be managed. Ask for examples of production pipelines, failure handling, data-quality checks and documentation, then test whether the proposed design fits your sources and users.
A Data Lake freelancer should clarify source systems, data ownership, expected workloads, security constraints, delivery boundaries and the current cloud or on-premises environment. They should also agree on success criteria, access arrangements, handover documentation and who will operate the platform after delivery.
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 877 € based on an 8-hour working day.
Of the freelancers in Austria who have used Data Lake in their recent projects, 90% hold at least a Bachelor's degree and 60% hold at least a Master's degree.
On average, freelancers in Austria who have used Data Lake in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 2.4 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 (31%).
The most common industries among freelancers in Austria who have used Data Lake in their recent projects are Information Technology (92%), Banking and Finance (77%), and Education (54%).
The most common business areas among freelancers in Austria who have used Data Lake in their recent projects are Information Technology (100%), Business Intelligence (85%), and Project Management (85%).
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 
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Philipp Thomaschewski
FRATCH CEO
