DAX Experts in Frankfurt
matched in minutes from over 15,000 CVsHire experts who create robust DAX measures, semantic models and Power BI reporting solutions, with the right skills for your data landscape. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Frankfurt, who have recently used DAX
Felix T.
Last position:
Data Engineering and Power BI at Wesernetz Bremen
Independently built a data platform with cross-system process monitoring.
- Designed the Bronze/Silver/Gold architecture and Python-based pipelines for diverse operational sources.
- Cleaned, harmonized, and validated data; processed and stored it in Parquet format.
- Tracked data history and built business-focused fact and dimension models for traceable reporting.
- Automated data delivery with Python and Power Automate (desktop and cloud); used SharePoint for archiving and data access.
- Developed the Power BI solution from data preparation through to visualizing process statuses, work progress, and deviations.
Technologies: Python, SQL, Parquet, Power BI, Power Query, Power Automate, SharePoint, Copilot
Torsten F.
Last position:
Data Analyst, Requirements Manager at Isabellenhütte Heusler GmbH
Analysis of the existing reporting platform, including processes and governance topics, with stakeholders from Sales and Marketing.
Detailed analysis and evaluation of customer-defined requirements for existing reporting and new dashboards to be established.
Support for stakeholders in managing sales processes and identifying KPI trends at an early stage.
Use of Microsoft Power BI as the central analysis and reporting platform.
Development of a proposal for the required further development of processes and the Power BI platform.
Documentation of AS-IS business processes and derivation of company-wide KPIs, including coordination with stakeholders.
Analysis and assessment of the customer's Power BI platform.
Analysis of processes and data governance.
Documentation of AS-IS business processes.
Development of recommendations for further developing processes and the reporting platform.
Design and implementation of dashboards in Power BI.
Development of company-wide KPIs and coordination with stakeholders.
Microsoft Power BI.
Data analytics.
KPI definition and reporting.
Dashboard design and data visualization.
Stakeholder management and requirements management.
Jana C.
Last position:
Freelance Business Intelligence Consultant at Superprof Germany & Upwork
- Design an interactive Tableau dashboard to analyze historical aviation accidents using data from the Federal Bureau of Aircraft Accident Investigation
- Develop visualizations to provide actionable insights to improve aviation safety measures employing data modeling and transformation techniques
- Develop a Power BI dashboard to monitor sales KPIs and product performance integrating data from multiple sources
- Design a star schema data model and implement advanced DAX measures for high-performance and dynamic reporting
- Design a comprehensive BI architecture solution focusing on ETL pipelines, data integration, and data governance
- Recommend Power BI as the central tool and create a security-compliant implementation roadmap
Ulm P.
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Zahra D.
Last position:
Data and Process Analyst in Healthcare at Ministry of Health and Medical Education
- Optimized the patient journey through big data analysis and cross-functional collaboration
- Regionalized NICU centers with 86% coverage using mathematical models
- Developed patient flow and geoprocessing models with Python and ArcGIS, resulting in an 18% increase in efficiency
- Built simulation models to optimize bed utilization and reduce waiting times with Rockwell Arena
- Developed analytical dashboards in collaboration with clinical experts
- Implemented machine learning algorithms for birth predictions and cross-functional prescription analyses
Judith B.
Last position:
BI & Analytics Consulting
- Analysis of web and campaign performance to derive actionable insights for marketing and growth optimization
- Implementation and maintenance of tag management solutions to ensure reliable and consistent data collection
- Continuous development and optimization of reporting structures with a focus on scalability and data quality
- Conducting regular deep-dive analyses and leading monthly stakeholder sessions to present results and align on optimization measures
- Design and operation of end-to-end data flows from data collection to visualization
- Tools: GA4, Google Tag Manager, Looker Studio, Airbyte, BigQuery
Benedikt R.
Last position:
Power BI developer at Mechanical Engineering (SME 500 emp.)
- KPI dashboards for inventory and goods received quality control & testing ETL, dataset, dataflows and report development, complex DAX solutions
Data sources: Dataverse, RDB, Excel
Tools: ETL, data modeling, data flows, Power Query, M, Power BI, complex DAX
- Capacity: 25%
Petru K.
Last position:
Architect & Technical Team Lead & Senior Developer at Goetel GmbH
- Design, architecture & development/programming of ETL/ELT data pipelines, DWH, BI solution
- Technical project lead, POC – proof-of-concept creation
- Liaison between business units and technical teams
- Azure DevOps Boards & Jira
- Data modeling & data engineering – data warehouse & data mart
- Azure (Data Factory, Azure SQL, Azure DevOps CI/CD, Azure Data Lake V2, Business Central REST API, OData API, OAuth2 tokens)
- SharePoint lists & API for ADF, Firebird DB, Postgres DB, DB2
- Power BI (Power Query), DAX, Excel PBI add-on, GIS data
- Automated ETL process monitoring/logging, performance monitoring, error monitoring – capturing & resolution
- Index performance tuning & statistics monitoring, Transact-SQL
- Data security – MFA (multi-factor authentication) & OAuth2, MS Graph, Azure networks & firewalls, gateways, roles, user groups – with read/write permissions
- Sources – Vario Bill, Camunda, Radius, Geo Database, OTRS, PAST, MS Dynamics Business Central, Azure Blob Data Lake, SharePoint lists
Discover over 15,000 top freelancers
Statistics of experts using DAX
Aggregated from the professional profiles of matched freelancers.
Experience
19 years (Germany: 16 years)
Position duration
1.9 years (Germany: 2.9 years)
Positions per freelancer
16 (Germany: 11)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Professional Services, Transportation
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
57% (Germany: 73%)
Doctorate
14% (Germany: 9%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 95%)
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 Frankfurt 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 Frankfurt using DAX
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.
DAX 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 (75%)
- Professional Services (75%)
- Transportation (63%)
- Energy (50%)
- Manufacturing (50%)
- Government and Administration (50%)
- Telecommunication (50%)
- Banking and Finance (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
DAX for business analytics
DAX, short for Data Analysis Expressions, is the formula language behind analytical models in Microsoft Power BI, Power Pivot and SQL Server Analysis Services Tabular. It helps teams define measures, calculated columns and tables for interactive reporting. Its evaluation context makes it possible to express time-based, filtered and business-specific calculations across connected data.
Models and measures
DAX specialists shape reliable semantic models rather than writing isolated formulas. They define relationships, hierarchies, calculation logic and reusable measures that support finance, sales, supply chain, marketing and operations reporting. Strong models keep business rules consistent across dashboards and self-service analysis.
- Create measures for revenue, margin, inventory and operational KPIs
- Apply filter, row and evaluation context correctly
- Build date tables and time-intelligence logic
- Refactor slow or duplicated expressions
Microsoft ecosystem
DAX work sits within the Microsoft data ecosystem. Professionals commonly connect Power BI models to SQL Server, Azure Synapse, Fabric, Excel Power Pivot and Analysis Services. They also work with Power Query and M for data preparation, while SQL remains important for shaping source data before it reaches the model.
When expertise matters
Companies bring in freelance DAX expertise when reports produce conflicting figures, models become difficult to maintain or performance declines as data grows. Specialists can support a new Power BI rollout, a migration from Excel or Analysis Services, a governed self-service model, or a focused improvement of existing reports. In Frankfurt, they may collaborate with local finance, manufacturing, logistics and service teams on-site or remotely.
Signs you need support
- Different reports show different definitions of the same KPI
- Measures return unexpected results under slicers or drill-downs
- Report interactions feel slow despite a suitable data source
- A Power BI model has grown without clear ownership
- Business users need governed self-service reporting
What strong specialists deliver
Good DAX professionals explain the business meaning behind every measure and test results against trusted source figures. They understand storage and formula engines, cardinality, context transition and model design, not just syntax. They document assumptions, keep calculations readable and work closely with data owners, analysts and report users so the final model remains useful after handover.
Frequently asked questions
Not sure where to start with DAX? These answers cover the essentials.
DAX is used to create calculations in Power BI, Power Pivot and SQL Server Analysis Services Tabular. Companies use it for measures, calculated columns, time analysis, dynamic filtering and business rules inside analytical models.
DAX calculates results within a semantic model and responds to filter and row context. SQL is usually used to retrieve and transform source data, while DAX is better suited to interactive measures that change with report selections. Strong projects often use both.
A capable DAX specialist should also understand Power BI data modeling, Power Query and M, SQL, dimensional design and report usability. Experience with Excel Power Pivot, Azure data services or Microsoft Fabric can be valuable when the wider environment requires it.
A focused measure adjustment may suit a professional with practical DAX experience, while a shared enterprise model needs deeper knowledge of relationships, context, governance and performance. The right level depends on model complexity, data quality and the consequences of incorrect reporting.
Yes. DAX projects are often handled remotely through shared workspaces, source-control practices, documentation and review sessions. On-site collaboration in Frankfurt can help when specialists must clarify business definitions with finance, operations or reporting teams.
Review whether DAX measures return trusted results across filters, drill paths and edge cases. Ask the specialist to explain evaluation context, model relationships and performance choices in clear business language. Readable formulas, documented assumptions and repeatable validation are strong quality signals.
A DAX freelancer is useful when a reporting deadline is close, an existing model is unreliable or internal analysts need specialist support. They can establish patterns, resolve complex calculation issues and transfer knowledge while the internal team retains ownership.
Not always. DAX professionals can often work effectively in English when requirements, model documentation and stakeholder reviews are handled in English. German language skills become more important when the role involves local business workshops, user training or close collaboration with German-speaking teams.
The average hourly rate of freelancers in Frankfurt, Germany who have used DAX in their recent projects is 96 €, which corresponds to a daily rate of about 768 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used DAX in their recent projects, 100% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used DAX in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Frankfurt, Germany who have used DAX in their recent projects are German (100%), English (100%), and French (50%).
The most common industries among freelancers in Frankfurt, Germany who have used DAX in their recent projects are Information Technology (75%), Professional Services (75%), and Transportation (63%).
The most common business areas among freelancers in Frankfurt, Germany who have used DAX in their recent projects are Business Intelligence (100%), Information Technology (88%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used DAX
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.
Berlin Hamburg Munich Cologne 
Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
Berlin 
Munich 
Cologne 
Dusseldorf 
Essen Countries:
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