
DAX Expert
for trusted Power BI models, matched in minutes with vetted and available freelancersHire experts who write efficient DAX measures, structure Power BI semantic models and improve reporting performance across Power BI, Excel and Analysis Services. FRATCH matches you quickly and precisely with vetted, available freelance professionals.
Meet FRATCH Experts who have recently used DAX
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company’s BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment using a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic in a central semantic model – elimination of redundant files, manual data transfers and inconsistent metrics across departments
- Forecasting & Planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enabling rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing and consistent modeling using Star Schema, DAX and Power Query
- Incident & Anomaly Analysis: Identification, investigation and explanation of data anomalies, including root-cause analysis and specific recommendations for action
- AI Solution Architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Development of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email delivery of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Tobias S W.
Last position:
CEO & Fouder at Wittbix
Christian P.
Last position:
Power BI Developer & Consultant in an Agile Team (SAFe) at DB InfraGO AG
Further Development of the Integrated Capacity Management Platform InKa
Rail Infrastructure
- Power BI shared datasets and reports via DirectQuery on Amazon Redshift (timetable, construction and capacity data)
- Automated report testing with Playwright in Docker containers, version control with GitLab
- Concept and implementation of user communication (information page, changelog, known bugs)
Initial Situation:
The integrated capacity management platform (InKa) is a monitoring and analysis platform for data from timetable and capacity management: customer orders, infrastructure, timetable operations, construction, as well as route capacity and width. The data is stored and linked in a structured data warehouse. This makes it possible to create complex KPIs across different source systems and display current and future route utilization as well as construction activity across the network. The goal is to improve strategic, medium-term and intra-year planning and provide users with easy access to capacity management analyses.
Measures:
- Enablement: Introduction of Power BI with training and workshops for development teams.
- Consulting & Design: Problem analysis, concepts and solution consulting for reporting requirements; implementation of reporting solution plans.
- Data Model: Development of shared datasets with DirectQuery on Amazon Redshift and import tables; DAX measures for utilization and capacity KPIs.
- Development: Data analysis, data transformation and visualization in Power BI; extension and migration of business applications to Power BI; AI-supported development in VS Code with GitHub Copilot.
- Test Automation: Automated testing of Power BI reports with Playwright; setup of the test environment in Docker containers.
- User Communication: Concept and implementation of a central information page with hot news, changelog and known bugs, access from reports with report filters, updates via Power Automate.
- Deployment: Management of Power BI Deployment Pipelines across the DEV, TEST and PROD environments.
- Agile Working: Work in an agile team according to SAFe (Scaled Agile Framework); refinement of user stories and features including effort estimates in Jira; version control with Git and GitLab.
- Quality & Documentation: Reviews for quality assurance, error analysis and resolution, technical documentation in AsciiDoc and Confluence.
Technologies: Power BI, DAX, Power Query, DirectQuery, Amazon Redshift, Git / GitLab, Deployment Pipelines, Playwright, Docker, AsciiDoc, Power Automate, Jira, Confluence, VS Code with GitHub Copilot, SAFe
Results:
- Capacity management KPIs from multiple source systems combined on one platform
- Transparency regarding current and future route utilization and construction activity across the network
- Easy access to analyses for users
- Automated regression testing of Power BI reports
- User communication implemented: central information page with hot news, changelog and known bugs, directly accessible from the reports
Vili D.
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility
Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture
Pipeline orchestration with Azure Data Factory
Improved and automated the development and deployment process by integrating Git and GitHub Actions
Technical leadership of the Data Engineering team (3 employees)
Led workshops to optimize and stabilize the data platform and development process
Collected and prioritized new requests and maintained the product backlog
Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural
Hachem S.
Last position:
Machine Learning & BI Lecturer at EU Business School
- Taught ML, BI, and Big Data to Master's students.
Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM
Stefan O.
Last position:
Founder at ProtocolEngine.io
Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.
- Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
- Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
- Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
- Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
- Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
- Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.
Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.
Adrian K.
Last position:
Senior Advisor, Process Governance & Transformation at MOIA GmbH
- Ran a group-wide steering committee to set strategic direction for a turnaround program. Planned delivery to secure go-to-market and investor milestones
- Prepared the project structure and supplier management process for an ACQ.4 Automotive SPICE audit. Built dry runs and compiled evidence with the team, resulting in a successful CL2 assessment
- Synchronized Automotive SPICE activities with the organization's SAFe rollout by screening base practices and agile artifacts for overlap. Avoided approximately 30% duplicate effort
Deepa K.
Last position:
Data Analyst – BI Lead Engineer at Novartis
- Leading enterprise BI transformation across Power BI & Microsoft Fabric, delivering scalable data models, automated reporting, and high-performance analytics solutions for commercial and operational leadership.
- Building and optimizing Power BI Dataflows, Fabric Lakehouse datasets, semantic models, and automated reporting pipelines to improve data scalability, governance, and reporting performance.
- Driving dashboard modernization and KPI governance by translating complex business requirements into executive-level insights, interactive visualizations, and decision-ready analytics.
- Designing end-to-end Microsoft Fabric architectures integrating data ingestion, transformation, virtualization, and enterprise reporting across cross-functional business domains with SAP BW to Qlik to Power BI migration.
- Delivering AI-enabled reporting capabilities, threshold-based alerting, and automation frameworks within the Power BI ecosystem to accelerate business decision-making.
- Partnering with commercial leadership, analytics teams, and IT stakeholders to standardize KPIs, optimize BI strategy, and deliver scalable, business-critical reporting solutions.
- Recognized for combining strong stakeholder leadership, technical architecture expertise, and business-driven analytics to deliver impactful enterprise BI transformation initiatives.
Sarvesh L.
Last position:
Data Analytics for Renewable Energy Integration at Harz University
- Created data pipelines and visualization tools to support sustainable energy decision-making
- Developed insights that could optimize renewable energy deployment and grid integration strategies
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
Nisanthan S.
Last position:
Business Intelligence Consultant (freelance) at NBIC – Nisanthan BI Consulting
Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)
5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models
Proposal and feasibility assessments for BI and reporting projects
Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development
Custom ERP system
Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.
Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.
Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.
Timesheet app
Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.
Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.
Cash-flow modelling
Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.
Implementation: Built and extended the CF model to include project-development cash flows.
Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.
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.
Asım Y.
Last position:
Freelance BI/DWH/ETL Specialist at Akbank
- Setting architectural standards for Informatica Power Center development teams
- Maintenance-performance-health for DWH (Exadata) environments
- Qlik Sense / BO reports architectural standards
- Implementing best practices in ETL tasks
- Documentation ETL standards on Confluence
- Dynamic Data Masking rules for GDPR/KVKK regulations by using Informatica DDM tool
- DWH Data model Power Designer
- Upgrade Qlik Sense versions
- Merge all Informatica server's repository databases on one Oracle DB
Anshita S.
Last position:
Business Intelligence Developer and Data Analyst at Deloitte Consulting
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
Özlem A.
Last position:
Adjunct Lecturer at Whitecliffe University of Applied Sciences
- Teaching Introduction to Data Science Course in MBA Programme
Discover over 15,000 top freelancers
Statistics of experts using DAX
Aggregated from the professional profiles of matched freelancers.
Experience
16 years

Position duration
3 years

Positions per freelancer
11

Top business areas
Business Intelligence, Information Technology, Product Development

Top industries
Information Technology, Professional Services, Manufacturing

Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
98%
Master's degree or higher
72%
Doctorate
9%

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
95%
Based on our profile pool as of 5 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 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 5 Nov 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 (79%)
- Professional Services (53%)
- Manufacturing (43%)
- Banking and Finance (41%)
- Automotive (35%)
- Healthcare (35%)
- Retail (31%)
- Education (28%)
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 behind calculations in Power BI, Power Pivot and Analysis Services tabular models. It defines measures, calculated columns and calculated tables that turn structured business data into interactive analysis. Its evaluation context makes filtering, time intelligence and relationships central to every result.
Core capabilities
DAX specialists work across the full analytical model, not just individual formulas. Typical deliverables include:
- Measures for revenue, margin, retention and operational KPIs
- Date tables and time-intelligence calculations
- Filter context and row context corrections
- Calculated tables, columns and reusable calculation groups
- Model checks that prevent misleading totals and inconsistent filters
Ecosystem and tooling
DAX is closely connected to Power BI Desktop, Power BI Service, Excel Power Pivot and Azure Analysis Services. Strong professionals also use Tabular Editor, DAX Studio and VertiPaq Analyzer to inspect query plans, format models, manage metadata and identify storage or formula-engine bottlenecks. SQL, Power Query M and dimensional modeling often sit beside DAX in the same delivery.
When companies need help
Companies usually bring in freelance DAX expertise when a report has grown beyond simple formulas or when users no longer trust its numbers. Specialists can reshape a semantic model, replace slow calculated columns, reconcile measures with source data and prepare governed datasets for self-service reporting. They are also useful during migrations from Excel or legacy tabular models to Power BI.
What strong specialists deliver
Quality is visible in both the result and the model behind it. A strong DAX professional names measures clearly, separates business logic from presentation, handles filter behavior deliberately and explains why a calculation returns its result. They test totals, drill-through paths, inactive relationships and different slicer combinations instead of validating only the default report view.
Collaboration and handover
DAX work can be performed remotely when data access, security rules and business definitions are documented. Effective collaboration includes a clear measure catalogue, sample outputs, source-to-target definitions and review sessions with finance or operational stakeholders. Before handover, the specialist should document assumptions, refresh dependencies, performance findings and the steps needed to extend the model safely.
Frequently asked questions
Everything clients usually want to know about DAX, in one place.
DAX is used to express business calculations in Power BI, Power Pivot and Analysis Services tabular models. Companies use it for measures, calculated columns, calculated tables, time intelligence and filter-aware KPIs in interactive reports.
DAX calculates results inside a semantic model and responds to filter context as users interact with a report. SQL retrieves and shapes data at the source, while Power Query M prepares and transforms data before it enters the model; a strong solution often uses all three deliberately.
A capable DAX specialist should understand dimensional modeling, relationships, cardinality and star schemas. Experience with Power BI, Power Query M, SQL, Tabular Editor and DAX Studio helps connect formulas with ingestion, governance and performance work.
The right DAX experience depends on the model’s complexity, data quality and business risk. Straightforward measures may need focused formula work, while enterprise reporting usually calls for someone who can design the model, validate definitions, tune performance and guide stakeholders.
DAX projects are often suitable for remote collaboration when the professional receives secure access to representative data and clear business definitions. Workshops may still be useful for agreeing KPI logic, reviewing report behavior and resolving differences between source systems and published results.
Review whether DAX measures produce correct results under different filters, date selections, drill paths and relationship states. Also inspect naming, documentation, model structure, refresh behavior and query performance rather than judging a report only by its visual appearance.
DAX measures are generally preferable for values that should respond to report filters and keep the model lean. Calculated columns are evaluated during refresh and can be appropriate for row-level categories or stable attributes, but the choice should account for model size, refresh time and the required behavior.
DAX performance issues can be investigated with DAX Studio, Query View, Tabular Editor and VertiPaq Analyzer. These tools help separate formula-engine work from storage-engine work, inspect query plans, find expensive expressions and identify modeling choices that create unnecessary scans.
The average hourly rate of freelancers who have used DAX in their recent projects is 94 €, which corresponds to a daily rate of about 749 € based on an 8-hour working day.
Of the freelancers who have used DAX in their recent projects, 98% hold at least a Bachelor's degree, 72% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers who have used DAX in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers who have used DAX in their recent projects are German (99%), English (96%), and French (21%).
The most common industries among freelancers who have used DAX in their recent projects are Information Technology (79%), Professional Services (53%), and Manufacturing (43%).
The most common business areas among freelancers who have used DAX in their recent projects are Business Intelligence (98%), Information Technology (90%), and Product Development (62%).
Main locations of FRATCH Experts, who have recently used DAX
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
In Austria our freelancers and interim experts support companies from Vienna to Graz — on-site where your project needs them, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Countries:
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