DAX Expert in Frankfurt
in minutes with vetted and available freelancers matched by AIHire experts who create reliable Power BI semantic models, write efficient DAX measures and turn complex business logic into clear reports. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Frankfurt, who have recently used DAX
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 client-defined requirements for existing reporting and new dashboards.
Supporting stakeholders in managing sales processes and early detection of KPI trends.
Use of Microsoft Power BI as central analysis and reporting platform.
Developing a proposal for the necessary evolution of processes and the Power BI platform.
Gathering current business processes and defining company-wide KPIs in coordination with stakeholders.
Analysis and inventory of the client's Power BI platform.
Analysis of processes and data governance.
Recording and documenting current business processes.
Developing recommendations for process and reporting platform improvements.
Designing and implementing dashboards in Power BI.
Defining company-wide KPIs and aligning them with stakeholders.
Microsoft Power BI.
Data analytics.
KPI definition and reporting.
Dashboard design and data visualization.
Stakeholder management and requirements management.
Saicharan K.
Last position:
Lead Product Manager at OysterHR Inc.
- Enabled over $5M in EOR revenue and scaled the new standalone global payroll product to 500% YoY growth in the past year, following its strategic launch and integration into the core platform two years prior by aligning leadership across Sales, Finance, and Operations
- Owned the Go-to-Market strategy and served as the primary domain expert for Sales; redefined the Ideal Customer Profile (ICP) and introduced new commercial packaging and pricing structures that successfully shifted the pipeline toward mid-market accounts, significantly increasing Average Contract Value
- Drove platform consolidation by collaborating with staff engineers and architects to unify global payroll and EOR solutions into a single HR platform, unlocking cross-sell opportunities and improving operational efficiency
- Realised a 75% reduction in payroll transactional costs by driving the financial automation domain across 100+ countries; transitioned operations from expensive third-party partners to high-efficiency in-house processing and automation, while ensuring 99%+ payroll accuracy
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%
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 findings and align on optimization measures
- Designing and managing end-to-end data flows from data collection to visualization
- Tools: GA4, Google Tag Manager, Looker Studio, Airbyte, BigQuery
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
2 years (Germany: 2.9 years)
Positions per freelancer
15 (Germany: 12)
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: 97%)
Master's degree or higher
71%
Doctorate
14% (Germany: 9%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 96%)
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 Frankfurt 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 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 19 Sep 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%)
- Manufacturing (50%)
- Government and Administration (50%)
- Telecommunication (50%)
- Energy (38%)
- Banking and Finance (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What DAX does
DAX, short for Data Analysis Expressions, is the formula language used in Power BI, Power Pivot and Analysis Services tabular models. It calculates measures, calculated columns and tables from relational business data. Unlike a simple spreadsheet formula, DAX evaluates filter context, row context and relationships across a semantic model.
Where it is used
Companies use DAX to turn sales, finance, operations and customer data into interactive analytical products.
- Build revenue, margin and year-over-year measures
- Compare actuals with budgets, forecasts and targets
- Create time-intelligence calculations for management reporting
- Prepare reusable KPIs for Power BI dashboards
In Frankfurt, DAX work often supports reporting across finance, logistics, manufacturing, professional services and other data-heavy operations.
Core ecosystem
Strong DAX work depends on more than formula syntax. Professionals commonly work with Power BI Desktop and Service, Power Pivot, Azure Analysis Services and Power BI semantic models. They also understand Power Query and M, SQL, star-schema design, data refresh, row-level security and deployment workflows.
A sound model usually matters more than a clever expression. Clear dimensions, consistent keys and well-defined relationships make measures easier to test and maintain.
When to bring in expertise
Freelance expertise is useful when reports are slow, definitions differ between departments or existing measures have become difficult to trust.
- Refactor complex measures and reduce unnecessary iteration
- Design a tabular model for a new reporting product
- Establish shared definitions for revenue, cost or customer metrics
- Diagnose filter-context and time-intelligence errors
Specialists can also support migrations from spreadsheets or legacy reporting tools and document the logic for internal teams.
What strong professionals deliver
The best DAX professionals begin with business definitions and data grain, then test results against known cases. They distinguish calculated columns from measures, explain context transition clearly and use variables to keep expressions readable. They inspect query plans and model structure when performance is a concern rather than masking the issue with isolated formula changes.
They also communicate assumptions, edge cases and ownership rules. That makes a Power BI model useful beyond its first report.
Collaboration in Frankfurt
DAX projects can be handled remotely when data access, security and review routines are well organised. On-site workshops in Frankfurt can help align finance, operations and reporting stakeholders around metric definitions and model priorities. German and English communication may both matter, depending on the teams and documentation involved.
Before engaging a freelancer, define the source systems, reporting audience, refresh expectations and key measures. Ask for examples of semantic models, performance investigations and validation methods rather than judging formula complexity alone.
Frequently asked questions
Not sure where to start with DAX? These answers cover the essentials.
DAX is used to create measures, calculated columns and calculated tables in Power BI semantic models. It supports business logic such as margins, rolling periods, rankings, targets and year-over-year comparisons. A specialist should connect each expression to a clear metric definition and data model.
DAX is designed for analytical models and evaluates filter context across related tables. SQL is primarily used to retrieve and transform data, while Excel formulas usually operate within a worksheet grid. The technologies often work together: SQL prepares reliable source data, DAX defines analytical behaviour and Excel may consume the resulting model.
A strong DAX professional usually understands Power BI modelling, Power Query and M, SQL, star schemas and data-refresh processes. Knowledge of row-level security, deployment pipelines and Azure Analysis Services can also matter. Business understanding is essential when measures represent finance, sales or operational rules.
The right level for DAX depends on the model and the risk of the reporting decisions. A focused measure correction may need less preparation than a new enterprise semantic model with security, multiple sources and strict reconciliation. Assess the scope through sample data, required measures, performance expectations and review responsibilities rather than a fixed experience label.
DAX work is often suitable for remote collaboration when access to Power BI workspaces, source systems and documentation is arranged securely. Workshops in Frankfurt can be useful for agreeing on metric definitions with finance and operational stakeholders. German or English communication should be clarified before the engagement starts.
Review whether DAX measures return correct results under different filters, dates, hierarchies and missing-data conditions. Ask the professional to explain the model grain, context behaviour and validation approach. Readable expressions, documented assumptions and sensible performance testing are stronger quality signals than formula length.
Unexpected DAX results often come from filter context, row context, context transition or an incorrect relationship between tables. Ambiguous date tables, duplicated keys and hidden filters can create similar symptoms. A careful investigation checks the semantic model and evaluation context before changing the measure.
DAX works across Power Pivot, Power BI and Analysis Services, but the surrounding product should match the collaboration and governance needs. Power Pivot can suit personal or small-team analysis, while Power BI is better for shared reports and managed distribution. Analysis Services may fit centrally governed tabular models with broader consumption requirements.
The average hourly rate of freelancers in Frankfurt, Germany who have used DAX in their recent projects is 93 €, which corresponds to a daily rate of about 743 € 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, 71% 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 2 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 (88%), 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.
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Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
Berlin 
Hamburg 
Munich 
Cologne 
Dusseldorf Request a free demo
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FRATCH CEO
