dbt Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used dbt
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
Mansharan K.
Last position:
MS Fabric | Power BI Consultant at Gropyus Technologies GmbH
- Architected an enterprise Fabric-based data-product governance framework, authoring data contracts and schema-validation KPIs to enforce completeness, freshness and SLA standards across reporting data products.
- Operationalized pipeline observability by integrating Dagster orchestration data into automated data-health reporting, proactively validating data integrity and pipeline reliability before production reporting layers refresh.
- Established BI-as-Code and end-to-end governance through Git-based version control, CI/CD and Alpha→GA release management, strengthening lineage, schema-drift detection and production change traceability.
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
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Michael B.
Last position:
Product Analytics Consultant - Trust & Safety at Kleinanzeigen
- Detecting fraud patterns and implementing effective anti-fraud rules while maintaining acceptable false positive rates to ensure a balance between safety and a frictionless user experience
- Supporting ideation and roll-out of new trust and safety features to the platform to block fraudulent activity and increase user awareness for fraud
- Supporting Product, Development and Customer Support with BI reports and further guidance to identify and fight fraud and policy violations
Nitin B.
Last position:
Financial Analytics Lead at Independent Consultant
Led FP&A tech transformation for a 9-figure business – from resolving legacy technical debt to leading AI-native EPM implementation
- Driving end-to-end FP&A transformation, from architecture redesign through EPM tool selection to rollout
- Ran evaluation of 12+ EPM platforms, from vendor negotiation to selection framework tied to long-term planning
- Diagnosed constraints in financial planning architecture, presented findings to the CFO, and secured executive mandate to redesign FP&A infrastructure from the ground up
Chisom N.
Last position:
Founder & Analytics Engineer
- Client — Podimo ApS (podcast & audiobook streaming): build the finance reporting layer on BigQuery + dbt + Airflow, including the core revenue-transaction fact tables used across finance reporting.
- API automation: design and build a BigQuery → Airflow → Microsoft Dynamics 365 Business Central REST-API pipeline to automate sales-invoice posting, with idempotency and master-data sync between systems.
- Delivery: sole engineer on the engagement — requirements, modelling, orchestration and stakeholder communication with the client finance team, end to end.
Bidya B.
Last position:
Product Manager – Payments & Platform at Pipedrive
CRM and revenue platform managing billing and subscription workflows.
- Scaled payments infrastructure across data products, direct debit expansion and automated abuse prevention, generating $416K in annualized operational savings ($8K/week) by eliminating redundant gateway calls.
- Owned backlog and sprint execution for autonomous checkout abuse detection pipelines, designing real-time risk guardrails and velocity heuristics that blocked card testing attacks.
- Architected enterprise billing migrator user stories and data reconciliation mechanisms, achieving zero-downtime subscription state transitions and cutting $60K in infrastructure overhead.
- Expanded European direct debit (SEPA) payment capabilities, managing cross-squad API dependencies and automated webhook error-handling to eliminate checkout friction.
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
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
Pierre-Jean A.
Last position:
Verification Engineer – Aviation at Tri.Merge GmbH
- Automated analysis of test script repositories using Python
- Set up a SQLite database for signal and value tracking
- Identified critical inconsistencies through ad hoc SQL queries
- Technologies: Python, SQLite, Excel/ODBC
Bardiya B.
Last position:
Data Scientist at Rewe Digital GmbH
Statistical Forecasting Algorithm
- Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
- Migration from R/On-premise to Python/Snowflake
- Productionalization on Snowflake in cooperation with data engineers & DevOps
Monitoring Dashboard
- Data engineering for preparation & provisioning of necessary data/resources on Snowflake
- Development & deployment of a Streamlit dashboard in Snowflake
ML-based Probabilistic Forecasting on Vertex AI
- Development of a ML-based probabilistic forecasting algorithm from scratch
- Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI
Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow
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
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
Discover over 15,000 top freelancers
Statistics of experts using dbt
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
1.8 years
Positions per freelancer
10
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
99%
Master's degree or higher
68%
Doctorate
9%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
99%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany 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.
Discover detailed dbt rate benchmarks:
Explore rate insightsAverage rates of experts in Germany using dbt
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
dbt 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 (86%)
- Banking and Finance (47%)
- Professional Services (46%)
- Retail (44%)
- Automotive (31%)
- Education (30%)
- Energy (30%)
- Healthcare (30%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What dbt does
dbt, short for data build tool, helps teams transform data inside a warehouse using modular SQL models. It brings software development practices such as testing, documentation, version control and code review to analytics work. Teams use it to create trusted datasets for reporting, planning and machine learning.
Core project work
- Designing staging, intermediate and mart models
- Converting complex SQL into reusable transformations
- Adding tests for keys, relationships, freshness and accepted values
- Building source documentation and data lineage
- Refactoring models for clarity, speed and maintainability
Strong dbt projects make business logic visible and repeatable. They separate raw sources from curated data products, so analysts and data teams can change transformations without losing control of dependencies.
Ecosystem and tooling
dbt works with warehouses and query engines such as Snowflake, BigQuery, Databricks, Redshift and PostgreSQL. Professionals often combine it with Git, CI pipelines, orchestration tools, BI systems and data quality services. The wider ecosystem includes dbt Core, the command-line project, and dbt Cloud for managed development, scheduling and observability.
When expertise helps
Companies bring in freelance dbt specialists when a warehouse migration has stalled, model logic has become difficult to govern or reporting teams disagree about definitions. They also need support when introducing tests, documentation, deployment workflows or a layered project structure. In Germany, dbt work may involve remote collaboration across locations, with clear English communication often important in international data teams.
- Establishing naming, folder and model conventions
- Migrating legacy SQL into maintainable dbt projects
- Improving warehouse costs and query performance
- Connecting dbt runs to orchestration and deployment
What strong specialists deliver
A strong professional understands both SQL transformation logic and the business meaning behind metrics. They can trace a dashboard number back to its source, explain dependencies clearly and choose tests that catch real defects rather than create noise. They also know when to use incremental models, snapshots, seeds, macros or packages.
Choosing the right fit
Review a specialist’s examples of model design, testing strategy, documentation and production release processes. Ask how they handle changing source schemas, slow queries, failing builds and conflicting metric definitions. The best fit can work within your warehouse, version-control process and communication style while leaving behind a project the internal team can extend.
Frequently asked questions
Quick answers to the questions that come up most around dbt.
dbt is used to transform and organize data inside a warehouse or lakehouse. Companies use it to build curated models for dashboards, financial reporting, operational analysis and downstream data products, while adding tests, documentation and lineage.
dbt focuses mainly on the transformation stage and runs SQL where the data already lives. Traditional ETL tools often move and transform data through graphical workflows, while dbt emphasizes modular code, version control, testing and review; many teams use it alongside ingestion and orchestration tools.
A strong dbt specialist usually brings advanced SQL, dimensional modeling and warehouse knowledge. Useful adjacent skills include Git, CI/CD, Python, orchestration with tools such as Airflow, and experience with BI definitions, data quality and cloud platforms.
The right level depends on the project scope rather than a fixed number of years. A small set of models may need a specialist who can establish clean conventions, while a large warehouse migration requires proven skills in dependency design, incremental processing, testing, deployment and stakeholder alignment.
dbt work is well suited to remote collaboration because projects are managed through code repositories, automated runs and documented models. Teams in Germany should agree on working hours, review practices, access to warehouse environments and whether German-language communication is needed for business stakeholders.
dbt Cloud adds managed development, scheduling, job management and observability around dbt projects. dbt Core can suit teams that want to operate the command-line workflow themselves, while the choice depends on governance needs, deployment preferences, security requirements and existing tooling.
Look for clear model layers, sensible naming, meaningful tests, current documentation and readable SQL. A capable dbt professional can explain lineage, handle schema changes, diagnose failed runs and show how the project remains maintainable as sources and metrics evolve.
A dbt specialist may deliver a project structure, staging and reporting models, reusable macros, source definitions, tests, documentation and deployment workflows. They can also review an existing project, improve performance, migrate legacy transformations or establish a reliable metric layer for analytics teams.
The average hourly rate of freelancers in Germany who have used dbt in their recent projects is 87 €, which corresponds to a daily rate of about 699 € based on an 8-hour working day.
Of the freelancers in Germany who have used dbt in their recent projects, 99% hold at least a Bachelor's degree, 68% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers in Germany who have used dbt in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Germany who have used dbt in their recent projects are German (99%), English (99%), and French (20%).
The most common industries among freelancers in Germany who have used dbt in their recent projects are Information Technology (86%), Banking and Finance (47%), and Professional Services (46%).
The most common business areas among freelancers in Germany who have used dbt in their recent projects are Business Intelligence (95%), Information Technology (95%), and Product Development (69%).
Main locations of FRATCH Experts, who have recently used dbt
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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Philipp Thomaschewski
FRATCH CEO
