Big Data Experts in Switzerland
to turn complex data into useful decisions, matched in minutes with vetted professionalsHire experts who design data platforms, build Apache Spark pipelines, and deliver analytics for high-volume information. Work with vetted, available freelancers matched precisely to your project and ready to collaborate across Switzerland.
Meet FRATCH Experts in Switzerland, who have recently used Big Data
Michael R.
Last position:
Project Manager, Hustler, & Hound “Project KPIs on the Internet” at Global-KPI
- Project management, Hustler (identifying the complete financial operations, including Sales, Pitching, Financial Analysis, & Business Models) and Hound (identifying real customer needs, including Research, & Analysis) to build an online project KPI system.
- The system enables users to make well-founded decisions to keep projects on track according to their key parameters or bring them back on track when there are negative deviations from the plan.
- Provision of a forecast in addition to the current status.
- Automatic calculation and display of KPIs based on project key parameters entered by the user.
- Skills: Project Management, Project KPIs.
- Problem Space: Co-Innovation Builder (CIB), Corporate Innovation Team Set Up, Team Profile/ Team Canvas, Design Thinking, highlighting people, creating customer personas, researching the market, defining the problem.
- Solution Space: Narrowing down the problem, how to turn ideas into solutions, how to turn solutions into a concept, customer journey, Business Model Canvas, Value Proposition Canvas, prototyping, fine-tuning the prototype and Business Model Canvas, final pitch.
Wolf P.
Last position:
Interim Head of IT-POS Base GK - SAP at Depot GDC
- Interim management of IT-POS based on GK and SAP for DEPOT GDC.
- Responsibility for the stability and further development of the POS base platform.
- Management of adaptations and rollouts in the POS environment in coordination with the SAP backend.
Peter P.
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%
Ursula M.
Last position:
Business Mentor at RoleModel Rebels
- Mentor female students and professionals in advancing their careers, particularly as aspiring tech entrepreneurs.
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.
Ned O.
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
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
Hrvoje K.
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
Tom D.
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 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Switzerland 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 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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Big Data 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 (90%)
- Banking and Finance (80%)
- Education (70%)
- Manufacturing (70%)
- Professional Services (70%)
- Energy (50%)
- Healthcare (40%)
- Insurance (40%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Big Data covers
Big Data describes methods and systems for collecting, storing, processing, and analysing datasets that are too large, fast, or varied for conventional tools. It supports batch and real-time workloads, combining structured records with logs, text, sensor readings, transactions, and events. The goal is reliable information that teams can use for decisions, automation, and new digital products.
Typical applications
Companies use Big Data where information arrives continuously or must be analysed across many sources:
- Customer behaviour, recommendations, and marketing analytics
- Fraud detection, risk modelling, and financial reporting
- Predictive maintenance from industrial and IoT data
- Supply chain planning, forecasting, and operational monitoring
- Large-scale search, personalisation, and event analysis
Ecosystem and tooling
The ecosystem often includes Apache Hadoop for distributed storage and processing, Apache Spark for fast analytics, and Kafka for event streaming. Cloud services such as Amazon S3, Google BigQuery, Microsoft Azure, and Databricks may provide managed storage, compute, and analytics. Strong specialists also work with SQL, Python, Scala, Java, data lakes, lakehouses, orchestration, and data quality controls.
When expertise matters
Freelance expertise is useful when a company must modernise a data warehouse, create a lakehouse, or connect fragmented sources without disrupting existing operations. Specialists can establish ingestion patterns, partitioning, schemas, access controls, and monitoring. They also help teams manage cloud costs, improve pipeline reliability, and prepare data for machine learning or business intelligence.
Switzerland projects
Swiss organisations in finance, insurance, pharmaceuticals, manufacturing, retail, transport, and public services often handle data with strict reliability and governance requirements. A specialist may need to align technical choices with internal security processes, audit expectations, and multilingual stakeholders. Remote collaboration can work well for design and delivery, while workshops or system handovers may benefit from on-site sessions in Switzerland.
Strong professionals
A capable Big Data professional connects architecture with measurable business needs instead of selecting tools in isolation. Look for experience with failure recovery, data lineage, schema evolution, testing, observability, and access management. Strong work includes clear documentation, reproducible deployments, sensible cost controls, and a practical plan for transferring knowledge to the internal team.
Frequently asked questions
Need clarity? These are the questions we hear most often about Big Data.
Big Data is used to process information that is too large, fast, or diverse for conventional systems. Common applications include fraud detection, customer analytics, recommendation systems, predictive maintenance, IoT processing, and operational forecasting.
Big Data environments can handle broader data types, distributed processing, and high-volume or real-time workloads. A traditional data warehouse is usually more structured and focused on governed reporting, although modern lakehouse systems increasingly combine both approaches.
A strong Big Data specialist often works with SQL, Python, Scala, cloud storage, data modelling, orchestration, and streaming. Experience with Apache Spark, Kafka, Databricks, machine learning workflows, security, and data visualisation can also be valuable, depending on the project.
The need depends on the risk and scope of the work. A focused pipeline improvement may need a specialist who can quickly diagnose and deliver, while a new data platform requires proven experience with architecture, governance, operations, and migration planning.
Big Data work is often suitable for remote collaboration because design, coding, monitoring, and documentation can be handled online. On-site workshops may still help with security reviews, stakeholder alignment, access to internal systems, and handover to Swiss teams.
Ask for evidence of reliable pipelines, clear data models, monitoring, recovery procedures, and documented ownership. A good Big Data professional explains trade-offs in plain language and connects technical choices to data freshness, accuracy, security, and operating cost.
Big Data solutions commonly use Apache Spark for distributed analytics and transformation, while Hadoop remains associated with distributed storage and processing components. The right choice depends on workload patterns, existing systems, cloud services, operational skills, and whether managed alternatives reduce maintenance.
A production-ready Big Data pipeline has tested transformations, controlled schemas, secure access, monitoring, alerting, lineage, and a recovery plan. It should also handle late or duplicate events, support controlled releases, and provide documentation that another professional can operate.
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
