
DAX Experts in Germany
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Meet FRATCH Experts in Germany, 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
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.
Volker H.
Last position:
Data Analyst at Optaro GmbH
Creation of workflows for generating the data basis for the article import of a web shop: combining data from several sources, analyzing the requirements, designing the process with Jupyter Notebooks and Knime. Also creating code for automation in Python using Polars and Pandas.
Processing the source data, filtering and merging the source files and creating the needed intermediate products, creating the upload files, plausibility checks, quality checks.
Technologies used: PyCharm, Python, Jupyter Notebooks, SQL, Knime. Pandas, Polars
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
12

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
97%
Master's degree or higher
71%
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 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany 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.
Discover detailed DAX rate benchmarks:
Explore rate insightsAverage rates of experts in Germany 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 (81%)
- Professional Services (57%)
- Manufacturing (47%)
- Banking and Finance (43%)
- Automotive (35%)
- Healthcare (35%)
- Retail (33%)
- 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 the formula language behind calculations in Microsoft Power BI, Power Pivot and SQL Server Analysis Services. It evaluates measures, calculated columns and calculated tables in a tabular data model. Unlike a simple spreadsheet formula, DAX works with filter context, row context and relationships between tables.
What it builds
DAX turns structured business data into reusable analytical logic. Companies use it for financial reporting, sales analysis, workforce planning, supply chain views and operational dashboards.
- Measures for revenue, margin, targets and variances
- Time intelligence for periods, trends and comparisons
- Dynamic segmentation and ranking
- KPI logic for interactive Power BI reports
Ecosystem and tooling
DAX specialists usually work across the Microsoft analytics stack. Their toolkit may include Power BI Desktop and Service, Tabular Editor, DAX Studio, SQL Server Data Tools, Excel Power Pivot and Analysis Services.
They also need to understand Power Query and M, SQL, star schemas, data gateways, deployment pipelines and workspace security. DAX Studio and server timings help them inspect queries and locate expensive calculations.
When companies need support
External expertise is useful when a model has grown difficult to maintain, reports return inconsistent figures or refreshes take too long. It also helps when an analytics team is moving from Excel reporting to governed Power BI models.
- Existing measures need review or refactoring
- A tabular model needs performance tuning
- Business definitions must become consistent calculations
- A reporting solution needs documentation and handover
Germany project context
Companies in Germany use DAX in reporting environments across manufacturing, retail, logistics, finance and professional services. Projects may involve German business terminology, distributed stakeholders and strict expectations for traceable calculations.
Remote collaboration works well when requirements, model ownership and review routines are clear. On-site workshops can help with discovery, while secure access, documentation and regular demos keep delivery practical across locations.
What strong experts deliver
Strong DAX professionals begin with the business definition, then validate the data model before writing formulas. They distinguish row context from filter context, use variables and readable naming, and avoid hiding poor modeling behind complex expressions.
They test totals and edge cases, compare results with trusted source data and measure query performance. They can explain why a calculation works, document assumptions and leave a model that other specialists can safely extend.
Frequently asked questions
Curious about DAX? Here are the answers that come up again and again.
DAX is used to create measures, calculated columns and calculated tables in Power BI, Power Pivot and tabular Analysis Services models. It supports business calculations such as margins, forecasts, period comparisons, rankings and target tracking.
Data Analysis Expressions is designed for calculations inside a tabular semantic model, while SQL is mainly used to retrieve and transform data. Excel formulas usually evaluate cell ranges, whereas DAX evaluates relationships and filter context across tables.
A strong DAX specialist should understand dimensional modeling, Power Query and M, SQL, Power BI deployment and data security. Experience with Tabular Editor, DAX Studio, gateways and Analysis Services is also useful for larger models.
The right level depends on the scope, not simply on the formula count. A focused measure review may need a specialist who can quickly diagnose context problems, while a new enterprise model calls for expertise in architecture, governance, performance and stakeholder workshops.
DAX work is often suitable for remote collaboration because models, requirements and review sessions can be shared securely. On-site sessions may still help when German-speaking stakeholders need workshops about definitions, reporting ownership or data quality.
DAX fits well when a company needs interactive analysis on a Power BI or tabular model with reusable business logic. A different approach may be better when calculations belong in an upstream data warehouse, when real-time processing is central or when the reporting tool is outside the Microsoft ecosystem.
Ask for clear model documentation, test cases and an explanation of filter context. Quality DAX work produces correct totals, performs efficiently at realistic data volumes and remains understandable when another specialist reviews or changes it.
A DAX freelancer should clarify the source systems, model structure, business definitions, refresh method, security rules and expected report behavior. They should also confirm access, review contacts, documentation standards and whether the task covers formulas only or the wider Power BI model.
The average hourly rate of freelancers in Germany who have used DAX in their recent projects is 95 €, which corresponds to a daily rate of about 759 € based on an 8-hour working day.
Of the freelancers in Germany who have used DAX in their recent projects, 97% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Germany 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 in Germany who have used DAX in their recent projects are German (100%), English (96%), and French (22%).
The most common industries among freelancers in Germany who have used DAX in their recent projects are Information Technology (81%), Professional Services (57%), and Manufacturing (47%).
The most common business areas among freelancers in Germany who have used DAX in their recent projects are Business Intelligence (97%), Information Technology (91%), and Product Development (58%).
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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