
DAX Experts
for trusted Power BI insights, matched in minutes with vetted freelance specialistsHire experts who create reliable DAX measures, optimize Power BI semantic models, and connect business logic to clear reports. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your project requirements.
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 featuring a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between 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; enables 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 concrete recommendations for action
- AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Creation 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 distribution 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
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.
Tobias W.
Last position:
CEO & Fouder at Wittbix
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.
Oleg O.
Last position:
Senior Software Developer / BI Integration Developer Power BI, C# at Telecommunications
Embedded Analytics & AI-assisted BI
Design and development of an integrated analytics solution based on ASP.NET Core, Power BI Embedded, and LLM services to provide context-based business information.
Development of an AI agent with Function/Tool Calling for the secure orchestration of REST APIs, SQL data sources, and technical services within defined business processes.
Building automated BI workflows including workspace management, deployment processes, and scheduled refresh via the Power BI REST API.
Implementation of secure service-to-service communication with Microsoft Entra ID and Service Principal, and integration into existing enterprise system landscapes.
Technologies: ASP.NET Core, C#/.NET, Power BI Embedded, Power BI REST API, LLM API, AI Agents, Function/Tool Calling, Entra ID
Varsha P.
Last position:
Senior Data Analyst at Infosys
Enterprise Analytics Modernization – Germany-based enterprise reporting platform for operations and management analytics, used by 1,000+ internal users across multiple departments.
- Lead end-to-end Power BI and Microsoft Fabric reporting initiatives, delivering scalable dashboards and semantic models supporting daily operational and strategic decisions, achieving 30% faster decision turnaround and 25% reporting efficiency gains.
- Designed unified enterprise datasets using Microsoft Fabric Lakehouse and OneLake, automating historical data processing and reducing manual reporting effort by 40%.
- Built and maintained automated ingestion pipelines using Fabric Dataflows Gen2 and Data Pipelines, improving data refresh reliability to 99.8% uptime and ensuring consistent data quality.
- Implemented enterprise reporting governance, including Row-Level Security (RLS), workspace strategy, deployment pipelines, and documentation, increasing dashboard adoption by 35%.
Technologies used: Power BI, Microsoft Fabric, DAX, Power Query, SQL, Azure Data Fundamentals, Semantic Modeling, RLS, Agile
Daryoosh D.
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
Ajay Kumar D.
Last position:
Senior BI and Analytics Engineer at Novartis
- Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
- Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
- Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
- Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
- Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
- Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
- Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
- Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
- Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.
Marco T.
Last position:
Scrum Master at Siemens Energy
- Responsible for introducing agile methods within the Interface & Integration Team (2 Scrum Teams)
- Planning and delivering trainings in agile methods
- Facilitating workshops and Scrum events
- Removing impediments
- Increasing sprint performance
Hervé T.
Last position:
Senior Data Engineer at Schweizerische Post AG
Tools: Fabric, AWS, dbt, Power BI, SQL, DWH, R, Python
- Supported customers in implementing an architecture design for extracting and preparing data
- Planned the design and implementation of the BI and DWH platform
- Ensured the scalability and performance of the data platform
Yaroslav S.
Last position:
Senior Low-Code Consultant at Freelancer
Structured analysis and evaluation of business processes
Gathering, documenting, and prioritizing requirements
Creating business-friendly and technically executable process models
Use of Camunda tools
Deriving requirements and interfaces from BPMN diagrams
Coordination with stakeholders and business units
Translating business requirements into technical solution designs
Implementing efficient and tailored applications
Systematic collection, analysis, and documentation of requirements
Prioritizing and validating requirements in close collaboration with stakeholders
Alignment between business and development to ensure shared objectives
Creating use cases, user stories, and acceptance criteria
Continuous requirements and change management throughout the project lifecycle
Define project goals and create project plans
Delegate tasks and monitor project progress
Monitor budgets and inform stakeholders
Mendix: Architecture, development, and maintenance of custom applications (Microflows, Domain Model, Security, XPath)
Modeling Mendix workflows for process optimization
Develop scalable apps with Mendix including REST/SOAP integration with SAP, SQL, Azure & SharePoint
UI design for Mendix using Atlas UI, Fluent UI, HTML, CSS, JavaScript
Develop web & mobile apps with Mendix using agile methods (Scrum, Kanban)
Implement business logic with Mendix Microflows and Nanoflows
Performance optimization and architecture improvements for Mendix applications
Conduct Mendix training
Create technical documentation and best practices for Mendix
Coaching and mentoring for low-code development with Mendix
Philipp G.
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
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
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.
Discover over 15,000 top freelancers
Statistics of experts using DAX
Aggregated from the professional profiles of matched freelancers.
Experience
16 years

Position duration
2.9 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
96%
Based on our profile pool as of 26 Sep 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 26 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 (80%)
- Professional Services (55%)
- Manufacturing (46%)
- Banking and Finance (42%)
- Automotive (36%)
- Healthcare (34%)
- Retail (32%)
- Education (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What DAX is
DAX, short for Data Analysis Expressions, is a formula language for analytical models. It is used to define measures, calculated columns, calculated tables, and logic for time-aware business analysis. DAX works primarily with Microsoft Power BI, Power Pivot, and SQL Server Analysis Services Tabular models.
Where it is used
DAX turns structured business data into reusable metrics and interactive analysis. Companies use it for financial reporting, sales performance, inventory analysis, workforce planning, customer segmentation, and operational dashboards.
- Create measures for revenue, margin, growth, and forecasts
- Compare current results with prior periods and targets
- Build filter-aware KPIs for Power BI reports
- Support drill-down analysis across business dimensions
Ecosystem and tooling
Strong DAX work depends on more than writing formulas. Specialists work with Power BI Desktop and Service, Power Query and M, star schemas, relationships, row-level security, and deployment workflows. They may also use Tabular Editor, DAX Studio, SQL Server, Azure Analysis Services, or Microsoft Fabric.
When companies need help
Freelance expertise is useful when a model produces inconsistent figures, refreshes slowly, or has become difficult to extend. Companies also bring in specialists during a Power BI migration, a reporting standardization project, or the design of a governed semantic layer.
- Review inefficient measures and filter context
- Refactor models for clearer ownership and reuse
- Validate calculations against business definitions
- Improve refresh, query, and report performance
What strong specialists deliver
A strong DAX professional understands evaluation context, context transition, iterators, relationships, and date intelligence. They translate ambiguous business questions into tested measures and explain the result clearly to analysts and decision-makers. They also know when a problem belongs in the data model, Power Query, SQL, or the report rather than in a formula.
How projects succeed
Good delivery starts with agreed metric definitions, representative data, and a model that reflects the business grain. Remote collaboration works well when specialists can access documentation, sample outputs, and a secure development process; on-site work can help with workshops and stakeholder alignment. Quality is shown through readable formulas, fast queries, controlled permissions, and validation with the people who use the reports.
Frequently asked questions
Everything clients usually want to know about DAX, in one place.
DAX is used to create calculations in Power BI, Power Pivot, and Tabular models. It supports measures, calculated columns, time intelligence, filtering logic, and business KPIs that respond to report context.
DAX calculates results inside an analytical model and responds to filter and evaluation context. SQL is primarily used to retrieve and transform data at the database layer, so the two languages often work together rather than replace one another.
DAX is designed mainly for columnar Tabular models, while MDX is associated with multidimensional cube models. A specialist should understand the model type before deciding which language and calculation approach are appropriate.
A strong DAX freelancer usually understands data modeling, Power Query and M, SQL, Power BI visualization, and row-level security. Experience with Tabular Editor, DAX Studio, Microsoft Fabric, or Analysis Services can also be valuable for larger models.
A simple reporting model may need someone comfortable with core measures and relationships, while complex financial or operational models require deep knowledge of context, optimization, and governance. Assess the work by its model complexity, calculation risk, and stakeholder needs rather than by a fixed time threshold.
DAX projects are often suitable for remote collaboration because models, formulas, documentation, and validation results can be shared securely. Workshops, access controls, time zones, and the need for direct stakeholder sessions should determine whether occasional on-site work adds value.
Ask the DAX specialist to explain filter context, model grain, and the reason for each important measure. Review whether formulas are readable, results match agreed definitions, queries perform well, and the model remains maintainable when new data or reporting needs arrive.
A DAX specialist is a good choice when calculations are disputed, performance is poor, or a semantic model has become hard to maintain. A general Power BI professional may be sufficient for straightforward reports, but complex measure logic and model optimization call for deeper specialization.
The average hourly rate of freelancers who have used DAX in their recent projects is 95 €, which corresponds to a daily rate of about 758 € 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 2.9 years.
The most common languages among freelancers who have used DAX in their recent projects are German (100%), English (96%), and French (22%).
The most common industries among freelancers who have used DAX in their recent projects are Information Technology (80%), Professional Services (55%), and Manufacturing (46%).
The most common business areas among freelancers who have used DAX in their recent projects are Business Intelligence (97%), Information Technology (91%), and Product Development (60%).
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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