Google BigQuery Experts in Dusseldorf
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Meet FRATCH Experts in Dusseldorf, who have recently used Google BigQuery
Murad K.
Last position:
Senior AI/ML Engineer at Quantistry GmbH
- Led end-to-end delivery of ML/AI applications for the QuantistryLab simulation platform, from requirements definition and solution design to development, testing, deployment, and production support, coordinating efforts across back-end, DevOps, and ML teams
- Designed and implemented a compound search system with an open-weights LLM, the Pydantic AI agent framework, and the Model Context Protocol (MCP), exposing it through FastAPI endpoints
- Deployed and configured vLLM-based LLM serving on Kubernetes
- Built CI/CD pipelines and Helm charts to automate deployments across staging and production environments
- Instrumented the search system with OpenTelemetry spans and traces, integrating with the Honeycomb observability platform to monitor component-level latency and functional errors
- Developed a custom evaluation dataset and implemented evaluations for retrieval relevance, answer correctness, tool-call accuracy, and end-to-end task success
- Reduced infrared spectrum prediction time by 83% (from 60 to 10 minutes) by replacing a quantum-mechanical model with a pretrained graph neural network; fine-tuned the model using PyTorch, built and containerized the inference pipeline with Docker, and integrated it into the platform
- Implemented an MLflow model registry with MinIO-backed artifact storage
- Advised sales and science teams on ML/AI applications for prospective client projects, providing technical expertise to shape proposed solutions and prototypes
Technologies: AWS, Hetzner, Kubernetes, Helm, Docker, vLLM, Pydantic AI, MCP, Qwen, Llama 3, MLflow, MinIO, GitHub Actions, Python, FastAPI, OpenTelemetry, Honeycomb, PyTorch, Polars, pytest
Tim R.
Last position:
Marketing Measurement & Attribution Auditor at Redcare Pharmacy
Results:
- Identified weaknesses in the MMM setup and attribution as a whole
Responsibilities:
- Audits of Marketing Mix Modelling, Multi-Touch-Attribution, Incrementality Testing
Channels & Tools: SEA, Affiliate, TV, Adtriba MTA & MMM, Google Meridian MMM
Ehsan M.
Last position:
BI Developer at Telecommunications Infrastructure
- Gathered and analyzed requirements in close collaboration with business departments to develop data-driven solutions and scalable PowerBI reporting infrastructures.
- Conducted detailed error analyses and optimized existing semantic and data models to ensure a robust data architecture and high data quality and to improve PowerBI reporting.
- Developed and implemented scalable ETL processes for data preparation and integration.
- Built a wiki for table and view descriptions as well as PowerBI PowerQuery and KPI documentation to ensure a consistent understanding of data structures and key performance indicators.
Abdulrahman S.
Last position:
Senior Business Intelligence Analyst at ELEMENT Insurance AG
- AI-Enabled Analytics & Reporting: Lead a 2-person BI team, applying predictive analytics and automation to translate complex business requirements into forward-looking insights, recommendations, and financial reports.
- Advanced Data Visualization: Design and maintain 25+ high-impact Power BI/Tableau dashboards tracking company-wide KPIs and trends, structured to support predictive and automated reporting.
- Web Analytics & Insights: Own GA4 tracking and analysis, driving a 15% increase in conversion insight through deeper customer journey analysis.
- Data Pipeline Optimization: Partner with data engineers to redesign and automate data pipeline workflows, cutting manual reporting time by 20% while safeguarding data accuracy and system uptime.
Rüdiger K.
Last position:
Data Analyst and Reporting Manager at Energieversroger
Implemented Power BI reporting for various departments at an energy provider. Agile project: responsible for organizing and coordinating with departments and IT, and regularly presented interim steps and results to project management.
Sara W.
Last position:
Recruiting & Employer Branding Data Specialist at Sipgate
- Managed the entire hiring process with a focus on data-driven decision-making.
- Analyzed recruiting data using Excel and ATS to optimize processes effectively.
Discover over 15,000 top freelancers
Statistics of experts using Google BigQuery
Aggregated from the professional profiles of matched freelancers.
Experience
10 years (Germany: 13 years)
Position duration
1.2 years (Germany: 2.1 years)
Positions per freelancer
11 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Marketing
Top industries
Retail, Banking and Finance, Information Technology
Certification focus areas
Business Intelligence, Information Technology, Project Management
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
100% (Germany: 69%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Azerbaijani
Speak two or more languages
100% (Germany: 94%)
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 Dusseldorf 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 Dusseldorf using Google BigQuery
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.
Google BigQuery experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Retail (83%)
- Banking and Finance (67%)
- Information Technology (67%)
- Telecommunication (67%)
- Fashion (50%)
- Healthcare (50%)
- Automotive (33%)
- Cosmetics (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What BigQuery Does
Google BigQuery is a fully managed, serverless data warehouse for large-scale analytics. It lets teams query structured and semi-structured data with SQL, combine sources across Google Cloud and support dashboards, reporting, machine learning and operational decisions without managing database infrastructure.
Core Capabilities
BigQuery specialists shape data environments that remain secure, efficient and usable as demand grows. Typical deliverables include:
- Dataset, table and schema design
- ELT pipelines from cloud and business systems
- SQL models, views and scheduled queries
- Cost, partitioning and query performance controls
- Looker and business intelligence integrations
Google Cloud Ecosystem
BigQuery commonly works with Cloud Storage, Pub/Sub, Dataflow, Dataproc and Cloud Composer. Professionals may also use Dataform for SQL transformations, Looker for governed exploration, Vertex AI for analytical models and Google Cloud IAM for access control. Knowledge of APIs, service accounts and infrastructure automation helps connect the warehouse to wider environments.
When Specialists Help
Companies bring in freelance BigQuery experts when data is scattered, reporting is slow or an existing warehouse needs a safer operating model. They can modernize legacy SQL, establish data quality checks, migrate workloads from platforms such as Snowflake or Amazon Redshift and create documentation that internal teams can maintain. In Dusseldorf, remote collaboration often works well for cloud delivery, while workshops may benefit from on-site presence and German or English communication.
Strong Project Practice
Good professionals start with business questions, source-system constraints and expected data freshness rather than writing queries immediately. They separate raw, prepared and serving layers, define ownership and test transformations before dashboards depend on them. They also explain BigQuery billing drivers, use partitioning and clustering thoughtfully, and set monitoring for failed loads, schema changes and unusual query activity.
Choosing the Right Fit
Look for evidence of production work with BigQuery, not only familiarity with Google Cloud. A strong specialist can explain trade-offs between scheduled queries, Dataflow, Dataform and other pipeline options, and can show how access, lineage, testing and deployment are handled. Ask for a clear delivery plan, sample documentation and an approach to measuring data correctness, performance and ongoing operating cost.
Frequently asked questions
Not sure where to start with Google BigQuery? These answers cover the essentials.
Google BigQuery is used for cloud analytics, reporting, data exploration and machine learning preparation. It can combine information from applications, files, marketing tools and operational databases without requiring a company to run its own warehouse servers.
BigQuery is a serverless Google Cloud warehouse with separated storage and compute, while Snowflake and Amazon Redshift offer different approaches to resource management, governance and ecosystem integration. The right choice depends on existing cloud commitments, workload patterns, data-sharing needs, team skills and cost controls.
A strong Google BigQuery freelancer often brings advanced SQL, dimensional modeling, data quality practices and pipeline design. Useful adjacent skills include Cloud Storage, Dataflow, Pub/Sub, Dataform, Looker, IAM, Python and infrastructure automation.
The required level depends on scope. A focused reporting or SQL modeling assignment may need a specialist who can work within an established environment, while a migration, governance program or high-volume pipeline needs proven production experience with BigQuery, Google Cloud security and operational monitoring.
Yes. BigQuery projects are often suitable for remote collaboration because the work happens in cloud environments, repositories and shared documentation. On-site sessions in Dusseldorf can still help with stakeholder workshops, source-system discovery and knowledge transfer, with German or English agreed in advance.
Review how the specialist handles data modeling, tests, lineage, permissions, query performance and cost visibility. Ask them to explain failure recovery and schema changes in practical terms; strong BigQuery professionals make these controls clear before delivery.
Google BigQuery is usually a better fit for analytical workloads that scan diverse or growing datasets and serve many reporting or exploration needs. A transactional database remains more appropriate for frequent row-level application updates, strict operational transactions and low-latency serving.
A BigQuery specialist should clarify data sources, ownership, freshness expectations, access boundaries, query volumes, reporting users and deployment practices. They should also confirm whether the assignment covers migration, pipeline operations, dashboards, machine learning preparation or only SQL development.
The average hourly rate of freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects is 77 €, which corresponds to a daily rate of about 614 € based on an 8-hour working day.
Of the freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects, 100% hold at least a Bachelor's degree and 100% hold at least a Master's degree.
On average, freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 1.2 years.
The most common languages among freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects are German (100%), English (100%), and Azerbaijani (17%).
The most common industries among freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects are Retail (83%), Banking and Finance (67%), and Information Technology (67%).
The most common business areas among freelancers in Dusseldorf, Germany who have used Google BigQuery in their recent projects are Business Intelligence (100%), Information Technology (67%), and Marketing (50%).
Main locations of FRATCH Experts, who have recently used Google BigQuery
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.
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