Data Warehouse Experts in Zurich
, matched in minutes by AI from over 15,000 CVsHire experts who design reliable data models, build ELT pipelines and connect cloud warehouses such as Snowflake, BigQuery and Amazon Redshift. FRATCH matches you quickly with vetted, available freelancers whose experience fits your data landscape.
Meet FRATCH Experts in Zurich, who have recently used Data Warehouse
Marco S.
Last position:
MS Power BI Developer at Bayern Facility Management GmbH
Power BI development and administration, training, consulting, data modeling, DAX development
MS Fabric, MS Power BI, DAX
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
- Reduced UCC usage by 10%
- Developing automation scripts using Python
- Performance tuning
- Reduced development databases from 6 TB to 3 TB using Exadata columnar compression
- Improved application performance by 30% using the inmemory option
- Improved non-production Exadata performance by 20% to free up CPU resources before ExaCC migration
- Database patching of Oracle 19c
- Basic Ansible scripting for deployments and database cloning
- Developing an accounting model for a shared Oracle platform
- Migrating single-instance databases to Oracle RAC
- Analysis of RAC issues
- Advising development teams on how to migrate to RAC
Charles S.
Last position:
Data Delivery Lead at Westpac
- Owned and managed the product roadmap and backlog for the Consumer Banker reporting framework, prioritising features and driving iterative delivery of banker scorecards and network performance reporting in an agile environment.
- Developed and iterated portfolio financial reporting on a weekly cadence based on stakeholder feedback, replacing manual PowerPoint packs and saving the program hours of effort weekly.
- Integrated Generative AI (MS Copilot) to automate data lineage documentation across a large legacy codebase, eliminating est. 6 months of analyst effort and accelerating data governance outcomes.
- Led a unified data delivery approach and standards across five UNITE initiatives (~CHF 115m portfolio) supporting consolidation of legacy systems into the Digital Banker platform.
- Led cross-functional delivery team of 3 while also drawing on BA and DA talent pools, coordinating analytical resource across workstreams to accelerate data, reporting & governance outcomes.
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
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
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).
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
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
Revealed U.
Last position:
Executive Enterprise Data & Analytics Advisor at A medium-size private bank
- Responsible for defining and implementing an enterprise Data Governance framework with an initial focus on BCBS-239, including Data Catalog tooling and formalized data asset ownership.
- Led the turnaround and delivery of an Enterprise Data Warehouse to support regulatory and management reporting on a robust, integrated data platform with a primary focus on Finance.
- Served as a key contributor to the bank’s Data, Analytics & AI strategy, which was subsequently approved by the management board.
Nenad T.
Last position:
Contractor at Swisscom
- SAP Data Designer ETL, SQL Server, Docker for PharmaSuisse Data Warehouse Application (Application Manager and Developer)
- SAP Business Objects, ABAP on SAP HANA for the Police of the Canton of Bern (Application Manager and Developer)
- Avaloq Connectors to SAP BW for Banque Cantonale de Fribourg
Tom D.
Last position:
Leader of Start-up programs
Udo W.
Last position:
Julius Bär
Application ownership and further development of test user management (TUM)
Areas of responsibility: Application ownership (Application Ownership / ITSO), application management, incident management, deployment / release management, requirements management, prioritization, further development, automation, and interface management
Technologies: SQL Server, Python, GitLab, UC4, Lieberman, Linux
Responsible for the operation and continuous development of a central application for managing more than 5.000 technical test users and their data.
Gathered and assessed business requirements, independently prioritized further development, and planned and coordinated implementation using agile methods and PI Planning, in close collaboration with the relevant business units and IT teams.
Expanded the central SQL Server database with additional information about test and real users, and integrated further applications through defined interfaces. The modular application used Python-based processing components, with execution and workflows controlled through UC4. This enabled data from different source systems to be automatically transferred, processed, and made available, as well as new test users to be created automatically.
Ensured reliable application operations and continuously optimized and automated existing processes.
Application ownership, modernization, and migration of incident management (TRANT)
Areas of responsibility: Application ownership (Application Ownership / ITSO), application management, incident management, deployment / release management, requirements management, software modernization, migration, interface integration, and quality assurance
Technologies: UC4, Jira, SQL Server, Oracle, Java, Python, Lieberman, Linux, Jai
Responsible for the operation and development of an application that automatically records, processes, and forwards technical incidents in various test environments.
Automated the creation of Jira incident tickets when UC4 workflows were blocked, including routing them to the relevant application managers.
Modernized the application by migrating from Java to Python, moving the database from Microsoft SQL Server to Oracle, and replacing the Jenkins scheduler with UC4.
Integrated the Jira API and used the bank's internal AI solution Jai to support code migration and subsequent validation. Independently and critically reviewed AI-generated results for business and technical accuracy.
Shift lead for operations control in test environments
Areas of responsibility: Monitoring various test systems
Technologies: UC4, TSO, HOST, Azure-Cloud
Responsible for monitoring and controlling automated processing workflows in various test environments, including systems running in the Azure-Cloud.
Monitored UC4 and HOST workflows and analyzed and handled incidents. When processing workflows were blocked, Jira tickets were automatically created through TRANT and assigned to the relevant application owners. In coordination with them, affected jobs were restarted or stopped as needed. HOST processes were also monitored and controlled through OPC.
A multi-shift operation was introduced to ensure stable and as continuous as possible testing.
Test data anonymization manager
Areas of responsibility: Planning/anonymizing/publishing production data for test systems
Technologies: UC4, Informatica (PowerCenter and IDMC)
To ensure test environments could run with real data, production databases were cloned regularly. Production data had to be untraceable in test environments. For this reason, the cloned databases were first anonymized with Informatica PowerCenter and later with Informatica IDMC. Critical tables and columns in the various databases (Oracle, SQL-Server, MongoDB) had to be identified and analyzed at the data level. Rules for handling critical data were agreed with the application owners.
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
26 years
Position duration
2.2 years
Positions per freelancer
15
Top business areas
Information Technology, Project Management, Business Intelligence
Top industries
Banking and Finance, Information Technology, Insurance
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
80%
Certifications per freelancer
4
Most common languages
English, German, 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 Zurich 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 Zurich 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 29 Oct 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.
- Banking and Finance (93%)
- Information Technology (79%)
- Insurance (57%)
- Professional Services (57%)
- Education (36%)
- Healthcare (36%)
- Manufacturing (36%)
- Government and Administration (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 data from operational systems into a governed environment for reporting, analysis and business intelligence. It separates analytical workloads from production applications and gives teams consistent definitions for revenue, customers, products and performance. Modern warehouses may run in the cloud or alongside existing enterprise infrastructure.
Core Architecture
Strong specialists shape the full flow from source systems to trusted data products. They define dimensional or Data Vault models, choose batch or streaming patterns, and establish storage, compute and access layers. Common environments include Snowflake, Google BigQuery, Amazon Redshift, Microsoft Fabric and Databricks SQL, supported by SQL, Python and orchestration tools such as dbt and Airflow.
Typical Deliverables
Companies bring in freelance expertise for focused builds, migrations and improvements. Typical tasks include:
- Designing a warehouse model for finance, sales, product or operations data
- Building reliable ELT pipelines from applications, APIs and files
- Migrating workloads from on-premises databases to cloud platforms
- Creating dbt transformations, tests, documentation and deployment workflows
- Improving query performance, data freshness and warehouse cost control
When Expertise Matters
External specialists help when reporting projects are blocked by inconsistent definitions, fragile pipelines or slow queries. They can assess an existing warehouse, select an architecture for new requirements and create a practical delivery plan. In Zurich, they may work with banking, insurance, healthcare, retail and industrial teams, either on site or remotely, with clear communication across business and technical stakeholders.
Skills Around the Warehouse
Warehouse work depends on more than SQL. Valuable adjacent skills include source-system analysis, data integration, dimensional modelling, Python, cloud security, identity management and infrastructure as code. Professionals should also understand BI tools such as Power BI, Tableau or Looker, and know how to document ownership, lineage, quality rules and access policies.
Signs of Strong Specialists
The best professionals make analytical data dependable and understandable. Look for a clear approach to grain, keys, slowly changing dimensions, incremental loading and failure recovery. They explain trade-offs between freshness, complexity and cost, test transformations before release and leave behind maintainable models, monitoring and documentation. Ask for examples of measurable improvements in reliability, usability or delivery speed rather than polished dashboards alone.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Warehouse.
A data warehouse stores integrated, structured data for reporting, analytics and business intelligence. It helps teams compare information across systems using shared definitions and supports dashboards, financial reporting, forecasting and operational analysis without slowing transactional applications.
A data warehouse usually stores curated, structured data prepared for reliable analysis, while a data lake can retain raw data in many formats. The right choice depends on governance, query needs, data variety and how quickly information must become usable. Many modern architectures use both.
A strong Data Warehouse specialist often works with platforms such as Snowflake, BigQuery, Amazon Redshift, Microsoft Fabric or Databricks SQL. Relevant supporting tools include dbt, Airflow, Fivetran, SQL, Python, cloud storage and BI products such as Power BI, Tableau or Looker.
The right level depends on the scope, source systems and risk of the project. A focused transformation or modelling task may need a specialist who can work independently, while a migration or enterprise redesign calls for experience with architecture, governance, security and change management. Evaluate comparable delivery work rather than relying on a title alone.
Yes. Data Warehouse work is often well suited to remote collaboration because repositories, cloud consoles and documentation can be shared securely. Zurich teams should agree on working hours, communication routines, access controls and whether German or English is required for business and technical discussions.
Bring in a data warehouse freelancer when internal teams face a migration deadline, unreliable reporting, a new analytics initiative or a lack of specialist capacity. A freelancer can audit the current setup, deliver a defined workstream or support internal professionals without creating a permanent team structure.
Ask how the professional defines data grain, handles late or duplicate records, tests transformations and monitors pipeline failures. A capable Data Warehouse specialist can explain trade-offs clearly, show maintainable model and documentation practices, and connect technical choices to business reporting needs.
A sound data warehouse project should provide governed models, repeatable ingestion and transformation jobs, quality checks, access controls and clear documentation. It should also define ownership, lineage, refresh expectations and recovery procedures so future teams can trust and extend the analytical environment.
The average hourly rate of freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects is 124 €, which corresponds to a daily rate of about 994 € based on an 8-hour working day.
Of the freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects, 100% hold at least a Bachelor's degree and 80% hold at least a Master's degree.
On average, freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects have 26 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects are English (100%), German (93%), and French (50%).
The most common industries among freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects are Banking and Finance (93%), Information Technology (79%), and Insurance (57%).
The most common business areas among freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects are Information Technology (100%), Project Management (93%), and Business Intelligence (86%).
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.
Countries:
Zurich 
Geneva Basel Bern Request a free demo
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Philipp Thomaschewski
FRATCH CEO
