Data Warehouse Experts in Switzerland
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Meet FRATCH Experts in Switzerland, who have recently used Data Warehouse
Marco S.
Last position:
Business Analyst, Data Warehouse Developer at NRW.Bank
Business analysis for risk controlling.
Development of a data warehouse based on MS SQL Server with data from the FIS Cross-Asset Trading and Risk Platform (formerly Front Arena).
Implementation of ETL and transformation logic with T-SQL and Python (Jinja2 template engine).
Modeling and automation of data structures with Data Vault.
Creation of reporting and analysis reports with Microsoft Power BI, including user training and implementation.
Geoffrey G.
Last position:
Lead Researcher at York St John Business School
- Independently designed, conducted, and evaluated a research project examining dynamic management capabilities (DMCs) in the implementation of HR practices at different management levels (top, middle, and frontline management).
- Focus on the strategic role of frontline management in implementing effective HRM measures.
- Self-initiated project with academic collaboration from York St John University, Robert Kennedy College, and the University of Cambridge.
Markus F.
Last position:
Logistics Expert/Coach at RAPID Technic AG
- Coaching, developing fundamentals and leading technical aspects in logistics transformation
- Extending SAP WM functionalities
- Efficiency measures in shuttle warehouse technology
- Setting up logistics operations reporting
- Comprehensive inventory planning and execution
- Preparing the technical and commercial foundations for cooperation with external logistics service providers
- Recommendations for the future process and organizational structure
Reinhold S.
Last position:
Senior Software Developer at Hitachi Energy
- Support and further development of the Leegoo Builder
- Handling ad hoc requests
- Definition of rules/attributes and their rules
- Optimizing and managing SQL queries
Max R.
Last position:
ICT Solution Architect Senior at ewb, Energy, Water
- Questioning and discussion of technical requirements and coordination with the team
- Contributing to objectives of the Digital Transformation Services unit and implementation of objectives
- Analyzing, specifying, updating and delivering architecture models to implement digital solutions in line with business, data infrastructure and requirements
- Selecting suitable technical options for application design considering interoperability, reversibility, scalability, usability, accessibility and security and optimizing cost/quality ratio
- Creating and maintaining concept documents, architecture models and other technical documentation
- Reviewing services to be provided and other documents for solution development
- Collaborating with IT enterprise architect, business analyst, project manager, developers, testers and process owner in design and documentation of technical specifications for new and further developments
- Communicating and supporting concepts to relevant stakeholders
- Participating in enterprise architecture activities and ensuring compliance with principles, standards and guidelines
- Monitoring compliance with defined design at application, solution and enterprise level
- Developing and testing existing and new solutions as required
- Supporting and guiding development teams in implementation of new projects or maintenance of existing products, assuming product manager role if required
- Establishing and ensuring best practice in implementation, documentation, testing and packaging for distribution
- Contributing to handling of reported incidents and requests assigned to third level support and follow-up actions as required
Claus N.
Last position:
Oracle Database Engineer at BBV.ch
- Migration of databases from ODA to ExaData
- Migration of databases from ExaData to ExaCC/OCI
- Decreased UCC usage by 10%
- Developing automation scripts using Python
- Performance tuning
- Shrunk development databases from 6 TB to 3 TB using Exadata columnar compression
- Tuned application performance by 30% using inmemory option
- Tuned non-production Exadata by 20% to release CPU resources before ExaCC migration
- Database patching of Oracle 19c
- Basic Ansible scripting for deployments and database cloning
- Developing acconting model for shared Oracle platform
- Migrating single-instance databases to Oracle RAC
- Analysis of RAC issues
- Advising development teams of how to migrate to RAC
Stefan H.
Last position:
Senior Project Manager at Bechtle Schweiz AG
- Led multiple client projects according to the PRINCE2 standard in the healthcare sector, focusing on migrating existing infrastructures and applications to Bechtle Clouds
- Technologies used: MS Azure, Azure AVD, Exchange Online, SharePoint Online, Intune, Autopilot, Meraki vMX Firewall, and Bechtle Smart Workplace
- Improved and documented project-related processes
Stefan L.
Last position:
Senior Manager, Project Manager, Auditor and Consultant at Laager Consulting GmbH
Many years of experience in application development, ICT infrastructures, systems management, hardware and software, telecommunications, ICT strategies, business models, database management, data center consolidations, support and call center setup
Since 1999 independent consultant and project manager: ICT strategies and governance, processes, audits, security, infrastructure (including cloud, DevOps and tools), data and output management, organizational restructurings, business project management and consulting in various industries
Generalist with analytical skills, strong communicator at all hierarchy levels, deployable as manager, coach, project manager or consultant
Matthias I.
Last position:
Fractional CTO (Principal Engineer / Technical Architect)
- Designed large-scale systems and APIs serving thousands of concurrent users.
- Refactored a 650k-LOC monolith and led full AWS migration for stable performance.
- Introduced SLO-based observability, improving reliability and recovery flow.
- Optimised cloud and databases, achieving significant cost and latency reduction.
- Delivered LLM, RAG, and document-automation pipelines adopted in production.
Deschances T.
Last position:
Senior Data Architect at Odd Parrot
- Supporting UBS Wealth Management as Senior Data Architect within a multi-year enterprise data mesh transformation.
- Guiding a strategic stream to design and implement a data product aligned with UBS’s enterprise-wide data mesh framework.
- Leading architecture definition, governance alignment, and cross-domain integration to ensure scalable, compliant, and reusable data products across global stakeholders.
- UBS – Global Wealth Management Data Product Architecture: Designed an enterprise-aligned data product spanning 26 countries, defining data contracts, metadata standards, and federated architecture patterns enabling cross-domain reuse across the bank.
- Defined cross-jurisdictional data policies and access controls to ensure compliance with regulatory requirements across multiple regions (EU, APAC, LATAM, CH).
Kalin S.
Last position:
Sr Data Engineer / Architect at Samsung Logistics
- Architected and implemented a structured three-layer enterprise data warehouse model in Azure, establishing a robust and scalable data environment.
- Migrated legacy stored procedures to streamlined Azure Data Factory (ADF) pipelines, enhancing data processing efficiency.
- Introduced comprehensive Git-based source control, ensuring rigorous version management and collaborative development practices.
- Established automated data quality frameworks with proactive monitoring and alerting, significantly improving data integrity and reliability.
- Spearheaded the design of an enterprise data model, enabling a self-service BI environment that empowered business teams with advanced analytics capabilities.
- Developed and delivered insightful dashboards and reports in Power BI, transforming raw data into actionable business insights.
- Technologies: Azure Data Factory (ADF), Azure, MS-SQL, DataVault 2.0, Git, Power BI, data quality automation, Agile/Scrum, data modeling, self-service BI, stakeholder management.
Ala L.
Last position:
VR/AR/ML Project Site Lead (contract by Experis) at Meta
- Acted as project lead in different internal projects, including the development and implementation of innovative solutions based on machine learning, virtual and augmented reality with the aim of providing great user experience
- Drove project planning, execution and reporting, designed risk mitigation and schedule adjustment plans to bring the projects on the green path
- Directed the process optimization and conducted project reviews by being the liaison between engineering teams and executive stakeholders
- Served as agile coach and led the scrum ceremonies such as daily stand-ups, sprint planning, sprint review and sprint retrospective
Oscar M.
Last position:
IT Specialist / DBA at Rothschild Private Swiss Bank
- Act as DBA SME for MS SQL Server and primary contact for MSSQL infrastructure and long-term technology roadmap in a critical 24/7 banking environment
- Maintain and evolve SQL infrastructure and monitoring system across development, test, UAT, and production environments (10 servers, 4 always-active Windows clusters, MSSQL 2014–2022 on VMs hosted by Inventix)
- Automate SQL operations using Brent Ozar scripts, PowerShell, and Inventix cloud script integration
- Build and improve ETL processes and BI applications (Power BI); plan resources and mentor BI team
- Participate in review, delivery, and deployment of database improvements across the software development lifecycle
- Migrate SQL Server instances from 2017 to 2019 and 2022
- Integrate new applications requiring MSSQL databases
- Manage and support on-premise and Azure SQL Server solutions; advise on industry standards, best practices, and creative database solutions
- Develop automation scripts for internal systems using PowerShell and Git
- Monitor systems with Splunk and Grafana; manage alerts, filters, data ingestion, and dashboard configuration
- Collaborate with operations, development, and business teams to identify and resolve operational and performance issues proactively
- Implement new SQL Server technologies such as Query Store, Extended Events, Tuning Advisor, and system traces
- Provide on-call support and regular maintenance during evenings and weekends
- Define and enforce system policies and standards; work closely with application managers, HR, and IT platforms in Switzerland and the UK
- Handle 2nd/3rd level support service requests; document resolutions and cooperate with vendors
- Use internal and external monitoring tools to detect performance trends and implement alerts and processes to prevent database issues
- Document and share knowledge to improve technical understanding across operations and development teams; administer Confluence (installation, configuration, document management, performance, upgrades)
- Work professionally in cross-functional teams to advise, influence, and coach development and operations teams on database topics
Stefano B.
Last position:
CEO & Founder at wyse Business Solutions GmbH
Karl E.
Last position:
incl. CI/CD, automation at AALS Software AG
- Designed and delivered a practical real-time course on Flink and Hadoop with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, and Kafka
- Gained extensive DevOps and CI/CD experience
- Created ETL/ELT pipelines with Apache tools and Pentaho
- Led projects in municipal software, financial services, and big data with Kafka
- Developed AI/NLP models and chatbots with RASA, Chatter, and Dialogflow
- Built and managed a TypeDB knowledge database
- Worked with OpenStack, Kubernetes, and Podman
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
28 years
Position duration
3.2 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
Information Technology, Project Management, Product Development
Bachelor's degree or higher
81%
Master's degree or higher
69%
Certifications per freelancer
4
Most common languages
English, German, 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 Switzerland 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 Switzerland using Data Warehouse
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 Warehouse 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 (86%)
- Banking and Finance (68%)
- Professional Services (68%)
- Healthcare (50%)
- Manufacturing (50%)
- Government and Administration (41%)
- Insurance (36%)
- Transportation (36%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a data warehouse does
A data warehouse consolidates structured information from operational systems into a governed environment for reporting, analytics and decision-making. It separates analytical workloads from transactional applications and preserves trusted historical data. Modern warehouses may run in the cloud, on premises or across a hybrid landscape.
Core architecture
A strong warehouse design defines how data moves from source systems to usable business models. Experts work across ingestion, staging, transformation, storage and semantic layers. They choose between dimensional models, data vault approaches and wider lakehouse patterns according to data volume, change frequency and reporting needs.
- Map source systems and business definitions
- Design fact, dimension and semantic models
- Set up incremental loading and data quality checks
- Document lineage, ownership and access rules
Ecosystem and tooling
The ecosystem includes cloud data warehouses such as Snowflake, Google BigQuery, Amazon Redshift and Microsoft Fabric, alongside established platforms such as Microsoft SQL Server and Oracle. Delivery commonly involves dbt, Airflow, Dagster, Fivetran, Kafka, SQL and Python. Strong specialists connect these tools without losing control of security, cost or operational support.
Typical applications
Companies use data warehouses to create consistent views across finance, sales, supply chain, customer activity and product performance. They support dashboards, regulatory reporting, forecasting, experimentation and machine learning feature preparation. In Switzerland, projects often span multilingual teams, local operations and strict expectations for data governance.
- Replace spreadsheet-based reporting with governed models
- Combine ERP, CRM, web and event data
- Create executive dashboards and self-service analytics
- Prepare reliable datasets for advanced analytics
When freelance expertise helps
Companies bring in freelance specialists when a warehouse migration has stalled, reporting definitions conflict or the existing team lacks capacity for a major release. They can assess a legacy enterprise data warehouse, establish a practical target architecture or stabilize pipelines before a critical reporting cycle. Remote collaboration works well when documentation, ownership and access are organized; on-site workshops can help align business and technical teams.
What strong specialists deliver
The best professionals connect technical decisions to measurable business use without hiding complexity behind dashboards. They write clear SQL, test transformations, monitor freshness and lineage, and design models that remain understandable as sources change. They also communicate trade-offs around performance, governance, resilience and cloud spending, then leave behind documentation and maintainable workflows.
Frequently asked questions
Questions about Data Warehouse? Start with the answers below.
A Data Warehouse brings information from operational sources into a structured environment for analytics, reporting and historical analysis. It gives teams consistent definitions for measures such as revenue, inventory or customer activity without placing reporting load on transactional systems.
A Data Warehouse usually stores curated, structured data that is ready for governed analysis, while a data lake can retain raw data in many formats. The distinction is less strict in lakehouse architectures, where teams combine low-cost raw storage with warehouse-style modeling and controls.
A strong Data Warehouse specialist often brings advanced SQL, dimensional modeling, ELT design and data quality practice. Useful adjacent skills include dbt, orchestration with Airflow or Dagster, cloud security, Python, BI tools and source-system knowledge such as ERP or CRM data.
The right Data Warehouse experience depends on the scope, source complexity and consequences of inaccurate reporting. A focused model or pipeline may need a specialist for a defined delivery phase, while a platform migration benefits from someone who has handled architecture, testing, governance and operational handover.
Yes, Data Warehouse work is well suited to remote collaboration when cloud access, documentation and decision ownership are clear. Swiss teams may still prefer on-site workshops for requirements, governance or stakeholder alignment, while day-to-day modeling and pipeline work can remain remote.
Common Data Warehouse platforms include Snowflake, Google BigQuery, Amazon Redshift, Microsoft Fabric, Microsoft SQL Server and Oracle. The best choice depends on existing cloud commitments, workload patterns, integration needs, governance requirements and the skills already available to the company.
Ask a Data Warehouse specialist to explain a past model, the decisions behind it and how quality was monitored after launch. Look for clear reasoning about grain, lineage, testing, access control, failure recovery and business definitions rather than a tool list alone.
A Data Warehouse engagement may produce a target architecture, source mapping, dimensional or vault models, transformation workflows and tested reporting datasets. It should also include documentation, lineage, monitoring, handover guidance and clear ownership for future changes.
The average hourly rate of freelancers in Switzerland who have used Data Warehouse in their recent projects is 123 €, which corresponds to a daily rate of about 987 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Data Warehouse in their recent projects, 81% hold at least a Bachelor's degree and 69% hold at least a Master's degree.
On average, freelancers in Switzerland who have used Data Warehouse in their recent projects have 28 years of professional experience, with a single engagement typically lasting around 3.2 years.
The most common languages among freelancers in Switzerland who have used Data Warehouse in their recent projects are English (100%), German (91%), and French (50%).
The most common industries among freelancers in Switzerland who have used Data Warehouse in their recent projects are Information Technology (86%), Banking and Finance (68%), and Professional Services (68%).
The most common business areas among freelancers in Switzerland who have used Data Warehouse in their recent projects are Information Technology (100%), Project Management (86%), and Business Intelligence (77%).
Main locations of FRATCH Experts, who have recently used Data Warehouse
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.
Zurich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
