Data Lake Experts in Vienna
for trusted analytics foundations, matched in minutes with vetted freelance professionalsHire experts who design scalable data storage, build ingestion pipelines and connect cloud analytics services such as Amazon S3, Azure Data Lake Storage and Databricks. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Vienna, 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
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
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)
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
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
25 years
Position duration
2.8 years
Positions per freelancer
15
Top business areas
Information Technology, Project Management, Business Intelligence
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Project Management, Information Technology, Business Intelligence
Bachelor's degree or higher
86%
Master's degree or higher
71%
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 Vienna 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 Vienna 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 (88%)
- Banking and Finance (75%)
- Professional Services (63%)
- Manufacturing (50%)
- Government and Administration (50%)
- Retail (50%)
- Telecommunication (50%)
- Education (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a Data Lake Provides
A data lake stores structured, semi-structured and unstructured data in its original form. Teams can centralize events, documents, logs, sensor streams and operational records before deciding how each source should be transformed. Unlike a traditional warehouse, a data lake supports flexible schemas and broad exploratory analysis.
Core Architecture
Strong data lake work covers storage, ingestion, cataloguing, governance and consumption. Specialists shape a layered architecture that keeps raw data traceable while making curated datasets reliable for reporting, machine learning and operational use. They also define ownership, retention and access rules.
- Design zones for raw, refined and curated data
- Build batch and streaming ingestion paths
- Add metadata, lineage and discovery controls
- Separate sensitive data with precise permissions
Ecosystem and Tooling
Projects may use Amazon S3, Azure Data Lake Storage or Google Cloud Storage as the foundation. Apache Spark, Databricks, Apache Kafka, Flink and dbt often support processing and transformation, while catalogs and orchestration tools keep pipelines discoverable and dependable. The right stack depends on volume, latency, compliance and team capability.
When Companies Need Specialists
Companies bring in freelance Data Lake professionals when a warehouse cannot handle new data types, when isolated sources prevent useful analysis, or when an existing lake has become difficult to trust. In Vienna, local teams may value on-site workshops for architecture decisions, with remote delivery for implementation and documentation.
- Consolidate data from applications, devices and business systems
- Migrate fragmented storage into a governed enterprise data lake
- Repair unreliable pipelines and unclear ownership
- Prepare trusted data for dashboards, forecasting or machine learning
Skills That Distinguish Strong Professionals
Experienced specialists understand data modelling, distributed processing, cloud security and infrastructure automation together. They test schema changes, monitor freshness and quality, and make failures visible rather than hiding them. They can explain trade-offs clearly to analysts, product teams and security stakeholders, in English and, where needed, German collaboration contexts.
Data Lake or Data Lakehouse
A data lake prioritizes flexible, low-cost storage and broad access to source data. A data warehouse emphasizes governed, structured analytics, while a lakehouse combines lake storage with warehouse-style reliability, transactions and performance. The strongest choice depends on query patterns, governance demands and the systems already in place.
Frequently asked questions
Everything clients usually want to know about Data Lake, in one place.
A data lake collects data from many sources in its native form, including application records, files, logs, events and sensor data. Companies use it for large-scale analytics, machine learning, exploration and downstream data products.
A data lake accepts varied data with flexible schemas, while a warehouse usually stores curated, structured data optimized for repeatable reporting. Many organizations use both: the lake preserves source data and the warehouse serves controlled business metrics.
A data lake is a strong fit when flexible storage and broad data access matter most. A lakehouse adds transaction support, stronger table management and warehouse-like query behavior, so it can suit teams that want one foundation for analytics and machine learning.
A Data Lake specialist should understand cloud storage, batch and streaming ingestion, distributed processing, data modelling and orchestration. Security, metadata management, infrastructure as code and observability are also important for production work.
A Data Lake project needs experience proportionate to its sources, governance needs, processing patterns and operational risk. A professional handling a production migration should be able to show reliable pipeline design, access controls, monitoring and recovery practices rather than only prototype work.
A Data Lake project can usually be delivered remotely when documentation, access and communication routines are clear. On-site workshops in Vienna can help with stakeholder alignment, source-system discovery and security decisions, while implementation can remain distributed.
A strong Data Lake professional explains how data quality, lineage, permissions, cost and failure recovery will be handled. Ask for a clear target architecture, practical delivery plan and examples of how they made pipelines observable and datasets trustworthy.
A Data Lake freelancer may deliver the target architecture, storage layout, ingestion pipelines, transformation jobs, catalog configuration and governance documentation. Depending on scope, they can also add monitoring, data quality checks, migration plans and handover sessions for the internal team.
The average hourly rate of freelancers in Vienna, Austria who have used Data Lake in their recent projects is 116 €, which corresponds to a daily rate of about 928 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Data Lake in their recent projects, 86% hold at least a Bachelor's degree and 71% hold at least a Master's degree.
On average, freelancers in Vienna, Austria who have used Data Lake in their recent projects have 25 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Vienna, Austria who have used Data Lake in their recent projects are German (100%), English (100%), and French (25%).
The most common industries among freelancers in Vienna, Austria who have used Data Lake in their recent projects are Information Technology (88%), Banking and Finance (75%), and Professional Services (63%).
The most common business areas among freelancers in Vienna, Austria who have used Data Lake in their recent projects are Information Technology (100%), Project Management (88%), and Business Intelligence (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.
Countries:
Vienna 
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