Data Warehouse Experts in Zurich
matched in minutes from over 15,000 CVsHire experts who design dimensional models, build reliable ELT pipelines and connect tools such as Snowflake, BigQuery, Amazon Redshift and dbt. FRATCH finds a precise match with vetted, available freelancers quickly.
Meet FRATCH Experts in Zurich, 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.
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
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
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
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
2.4 years
Positions per freelancer
15
Top business areas
Information Technology, Project Management, Business Intelligence
Top industries
Banking and Finance, Information Technology, Professional Services
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
75%
Certifications per freelancer
5
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 Zurich 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 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 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.
- Banking and Finance (92%)
- Information Technology (83%)
- Professional Services (67%)
- Insurance (50%)
- Education (42%)
- Healthcare (42%)
- Government and Administration (42%)
- Manufacturing (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a data warehouse does
A data warehouse centralizes structured business data for reporting, analysis and decision-making. It brings together information from applications, finance systems, customer platforms and operational databases, then stores it in a form suited to reliable querying. Unlike a transactional database, it is optimized for analytical workloads, historical context and consistent definitions.
Core architecture
A strong design separates ingestion, transformation, storage and consumption. Experts choose between cloud warehouses, lakehouse patterns and hybrid environments based on data volume, freshness, governance and existing systems. They define fact and dimension tables, grain, keys, slowly changing dimensions and semantic layers so metrics remain consistent across teams.
Ecosystem and tooling
The work often spans SQL, Python, orchestration, data quality and infrastructure. Common components include Snowflake, Google BigQuery, Amazon Redshift, Microsoft Fabric, Databricks, dbt, Airflow, Fivetran and cloud storage. Specialists also connect BI tools such as Tableau, Power BI or Looker and manage access through the surrounding cloud platform.
Typical delivery work
- Design a warehouse model for finance, sales, operations or customer data
- Build batch or streaming pipelines from APIs, SaaS tools and databases
- Migrate legacy reporting databases to a cloud warehouse
- Create dbt transformations, tests, documentation and deployment workflows
- Improve query performance, data freshness and warehouse cost control
When outside expertise helps
Companies bring in freelance specialists when reporting definitions conflict, a migration has stalled or internal teams need a dependable analytics foundation. They can also support a new BI rollout, merger data integration or a move from on-premises infrastructure to the cloud. In Zurich, remote work is common, while workshops may benefit from occasional on-site collaboration and clear English or German communication.
What distinguishes strong experts
The best professionals connect technical design with business meaning. They ask how revenue, customers, products and operational events should be defined before writing transformations. Look for experience with lineage, testing, monitoring, access controls, incremental loading and recovery plans, plus the ability to explain trade-offs to analysts and stakeholders. A credible delivery includes documented models, reproducible pipelines and clear ownership after handover.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Warehouse.
A data warehouse stores integrated, historical business data for analytics, dashboards and recurring reports. It gives teams a consistent place to compare performance across finance, sales, operations and customer activity without putting analytical workloads on transactional systems.
A data warehouse usually stores curated, structured data with defined models and trusted metrics. A data lake can hold raw structured, semi-structured or unstructured data, while a lakehouse combines parts of both approaches. The right choice depends on governance, workloads, data types and the need for fast business reporting.
A strong data warehouse specialist commonly works with SQL, Python, cloud infrastructure, orchestration and data quality practices. Experience with dbt, Airflow, streaming, APIs, identity management and BI tools is also valuable. They should understand both dimensional modeling and the business definitions behind key metrics.
Before hiring a data warehouse freelancer, clarify the main reporting problems, source systems, data owners, freshness needs and security constraints. Existing schemas, sample reports and known data-quality issues help the specialist estimate the work realistically. A clear target architecture is useful, but it can also be developed during discovery.
A data warehouse project needs enough experience to handle modeling decisions, pipeline failures, changing source data and stakeholder disagreements. A focused improvement may suit one specialist, while a migration or company-wide foundation may require several complementary skills. Judge the need by system complexity and risk rather than by a fixed timeline.
Yes, data warehouse work is often well suited to remote collaboration because design, SQL, pipeline development and documentation are digital. Regular workshops with Zurich-based stakeholders can still help with metric definitions, access decisions and handover. Agree on communication language, working hours and responsibilities before delivery begins.
Ask a data warehouse specialist to explain a past model, including grain, source changes, testing, lineage and recovery. Strong answers connect technical choices to business outcomes and describe how users validate data. Review a small proposed design or discovery plan rather than relying only on tool names in a profile.
Snowflake and BigQuery are cloud warehouse options that reduce infrastructure management and support elastic analytical workloads. A traditional warehouse may still fit strict existing controls, predictable workloads or established on-premises operations. The decision should consider data location, security, integration, workload patterns and the team’s operating skills.
The average hourly rate of freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects is 130 €, which corresponds to a daily rate of about 1,042 € 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 75% hold at least a Master's degree.
On average, freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects have 28 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects are English (100%), German (92%), and French (58%).
The most common industries among freelancers in Zurich, Switzerland who have used Data Warehouse in their recent projects are Banking and Finance (92%), Information Technology (83%), and Professional Services (67%).
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 (92%), and Business Intelligence (83%).
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
