Big Data Experts in Switzerland
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Meet FRATCH Experts in Switzerland, who have recently used Big Data
Wolf Preuster-Drews
Last position:
Interim Head of IT POS (GK & SAP) at Depot GDC
- Interim head of IT POS on GK and SAP basis for DEPOT GDC.
- Responsible for the stability and further development of the POS base platform.
- Managing adjustments and rollouts in the POS environment in coordination with the SAP backend.
Peter Puchalla
Last position:
Consultant Strategy & Digital at Polynova AG
- Designed the growth and digital strategy for an EU distributor
- Established a differentiation strategy focusing on horizontal portfolio expansion, ESG and SG&A cost reduction using new digital sales and service channels
- Offered same-day logistic delivery for key customers, increasing customer satisfaction by 25%
Michael Rödle
Last position:
Project Manager, Hustler, & Hound "Project Metrics on the Internet" at Global-KPI
- Project management, hustler (identifying the full financial picture including sales, pitching, financial analysis, & business models) and hound (identifying real customer needs including research & analysis) to build a project metrics system on the Internet.
- The system allows users to make informed decisions to keep projects on track according to key data or to realign them when they deviate negatively from the plan.
- Providing a forecast alongside the current status.
- Automatic calculation and display of metrics based on user-entered project key data.
- Skills: project management, project metrics.
- Problem space: Co-Innovation Builder (CIB), corporate innovation team setup, team profile / team canvas, design thinking, highlighting people, creating customer personas, market exploration, defining the problem.
- Solution space: narrowing the problem, how to turn ideas into solutions, how to turn solutions into a concept, customer journey, business model canvas, value proposition canvas, prototyping, refining the prototype and business model canvas, final pitch.
Ursula Maria Mayer
Last position:
Business Mentor at RoleModel Rebels
- Mentor female students and professionals in advancing their careers, particularly as aspiring tech entrepreneurs.
Kalin Stefanov
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.
Deschances Tchakounang Ndjomou
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).
Ned O’hara
Last position:
Tech Lead at R3leaf GmbH
- Autonomously drafted architecture and delivered production code at startup pace
- Wrangled diverse geospatial formats (NETCDF, GeoTIFF, GML) into unified standards and built scalable climate data visualisations from hundreds of GBs of geodata in a production web app
- Mentored developers, facilitated AI skill sharing, and contributed to competitive strategy with C-Level leadership
Hrvoje Kurtović
Last position:
Researcher, Investment Research Institute at Pictet Group
- Designed and implemented AI-enhanced macro-factor models improving asset allocation decisions across multi-asset portfolios
- Developed machine learning-based FX trading strategies, integrating macroeconomic and sentiment data to identify profit opportunities
- Models adopted by the investment committee to guide equity and currency exposure
- Collaborated with portfolio managers to translate analytical output into actionable investment insights
Karl Estermann
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
Tom Debus
Last position:
Leader of Start-up programs
Discover over 15,000 top freelancers
Statistics of experts using Big Data
Aggregated from the professional profiles of matched freelancers.
Experience
22 years
Position duration
2.5 years
Positions per freelancer
15
Top business areas
Information Technology, Business Intelligence, Marketing
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Project Management, Quality Assurance
Bachelor's degree or higher
100%
Master's degree or higher
75%
Doctorate
13%
Certifications per freelancer
3
Most common languages
English, German, French
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 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 Big Data
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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Big Data work
Big Data covers the storage, processing, and analysis of very large, fast-moving, or complex data sets. It is used to turn raw event streams, logs, sensor data, and business records into reliable outputs for reporting, machine learning, and operations.
Common stack
- Hadoop for distributed storage and batch processing
- Spark for large-scale data transformation and analytics
- Kafka or similar tools for streaming ingestion
- Data lakes and warehouse integration for shared access
Where it fits
Companies bring in Big Data specialists when standard databases no longer handle volume, variety, or speed well enough. Typical work includes building ingestion pipelines, preparing curated data sets, and supporting analytics platforms used by finance, retail, media, logistics, and industrial teams.
What strong experts do
Strong professionals think about schema design, pipeline reliability, partitioning, job performance, and data quality from the start. They can work across ETL and ELT flows, batch and streaming models, and cloud services such as AWS, Azure, or Google Cloud when the stack calls for it.
Why freelance help matters
Freelance experts are a good fit for migrations, platform rescue work, new reporting layers, and short-term capacity gaps. In Switzerland, they often support teams that need clear communication, careful documentation, and smooth collaboration with both local and remote stakeholders.
Hiring signals
- Clear experience with distributed storage and processing
- Strong SQL and data modeling habits
- Familiarity with Spark, Hadoop, and streaming tools
- Evidence of clean handover, testing, and monitoring
- Ability to explain trade-offs in plain language
Frequently asked questions
Need clarity? These are the questions we hear most often about Big Data.
Big Data usually means working with data sets that are too large, too fast, or too varied for a single system to handle well. Companies use it for pipelines, analytics, reporting, machine learning features, and operational monitoring. The goal is not just storage, but data that stays usable and trustworthy.
Big Data is the broader field, while Hadoop and Spark are common parts of the stack. Hadoop is often tied to distributed storage and batch processing, and Spark is widely used for faster transformations and analytics. A good freelancer should know how these tools fit into the whole data flow.
Big Data freelancers are useful when a team needs specialist help for a migration, a new data lake, a streaming pipeline, or a system that has become slow or unstable. They are also a good choice when the internal team needs extra capacity for a specific delivery phase. Short, focused engagements often work well.
A strong Big Data specialist usually brings SQL, data modeling, and scripting skills such as Python or Scala. Cloud knowledge matters too, especially when the work runs on AWS, Azure, or Google Cloud. Monitoring, testing, and clear documentation are also important.
Big Data projects need more than tool knowledge. The right expert should understand distributed systems, data quality, failure handling, and performance trade-offs. Smaller reporting jobs may need less depth, but production pipelines and platform changes need proven hands-on experience.
Look for clear examples of pipelines that stayed reliable in production, not just proof of tool use. A strong Big Data professional can explain why they chose a certain storage layout, processing pattern, or stream design. Good signs also include testing, monitoring, and clean handover.
Yes, many Big Data specialists work well remotely, especially when the stack is cloud-based and the team has clear access and review processes. On-site collaboration can still help during discovery, architecture decisions, or stakeholder workshops. For Swiss teams, strong written communication in English is often enough, and German or French can be a plus depending on the setting.
Big Data focuses on handling large-scale data storage and processing challenges, while data engineering is the broader practice of building and maintaining data systems. In practice, the two overlap a lot. Many freelancers work across both, especially when they build pipelines, lakes, and analytics layers.
The average hourly rate of freelancers in Switzerland who have used Big Data in their recent projects is 134 €, which corresponds to a daily rate of about 1,071 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Big Data in their recent projects, 100% hold at least a Bachelor's degree, 75% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Switzerland who have used Big Data in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Switzerland who have used Big Data in their recent projects are English (100%), German (80%), and French (40%).
The most common industries among freelancers in Switzerland who have used Big Data in their recent projects are Information Technology (90%), Banking and Finance (80%), and Education (70%).
The most common business areas among freelancers in Switzerland who have used Big Data in their recent projects are Information Technology (90%), Business Intelligence (80%), and Marketing (80%).
Main locations of FRATCH Experts, who have recently used Big Data
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
