dbt Experts in Frankfurt
for trusted analytics pipelines, matched in minutes with vetted professionalsHire experts who turn warehouse data into tested, documented models with dbt, SQL and modern transformation workflows. Get precise access to vetted, available freelancers matched to your project quickly.
Meet FRATCH Experts in Frankfurt, who have recently used dbt
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
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
Silke D.
Last position:
Business Analyst at Rentenservice
Developed a digitalization strategy Analyzed legacy systems and designed a new IT landscape
- Gathered current work structures and processes
- Identified optimization opportunities
- Developed a tool landscape to support business processes
- Created a request for proposal
- Defined epics and user stories
- Modeled processes
Technologies/Methods: Confluence, MSTeams, MindManager, PlantUML, JIRA
Ulm P.
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Roman K.
Last position:
Senior Data Engineer / Cloud Architect at DB Systel
- Development of a central billing app for cloud costs at DB
- AWS
- Python
- AWS CDK
- RDS
- Spark (PySpark)
- Glue
- Lambda
- CI/CD (GitLab)
- React/Typescript
- data optimization
- Scrum
Markus G.
Last position:
Data Solution Architect, Founder at GRITCON GmbH
- Design and development of modern cloud DWH & data platforms
- Data Vault automation
- Implementation of ELT and CI/CD processes
- Requirements analysis and data modeling
- Building an automated cloud data platform as a reference architecture for financial risk controlling (Snowflake, Data Vault, DBT, Python, GitHub) 2024-10-01 – 2025-06-30, Zurich
- DWH further development, operations and cloud migration (Data Vault, DBT, SAP Data Services, Alteryx, SQL Server, Azure Synapse) 2023-03-01 – 2025-06-30, Frankfurt
- Implementation of a global cloud data platform (Data Vault, WhereScape, Snowflake, AWS, Scrum) 2021-04-01 – 2023-12-31, Cologne
- Proof of concept for a global cloud data platform (Data Vault, Snowflake, Synapse, WhereScape, Azure, Scrum) 2022-04-01 – 2022-07-31, Bonn
- Implementation of a cloud data platform (Data Vault, Snowflake, WhereScape, AWS) 2021-07-01 – 2022-04-30, Karlsruhe
- Big data integration of all source systems related to the ITSM process (Data Vault, Snowflake, WhereScape, AWS, Scrum) 2021-01-01 – 2021-05-31, Prague
- Development and operation of a global self-service BI platform to display around 150 corporate KPIs (Data Vault, WhereScape, Postgres, Jenkins, Talend, AWS, Scrum) 2018-11-01 – 2020-12-31, Frankfurt
- Implementation of a DWH for price management and capacity forecasting in long-distance passenger transport (SAP BODS, SQL Server, AWS) 2017-10-01 – 2018-11-30, Frankfurt
- Introduction of SAP BODS and migration of the existing DWH (SAP, BODS, HANA, Oracle, Cognos) 2017-05-01 – 2017-10-31, Rastatt
Discover over 15,000 top freelancers
Statistics of experts using dbt
Aggregated from the professional profiles of matched freelancers.
Experience
20 years (Germany: 14 years)
Position duration
2.2 years (Germany: 1.8 years)
Positions per freelancer
14 (Germany: 10)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
80% (Germany: 99%)
Master's degree or higher
60% (Germany: 68%)
Doctorate
20% (Germany: 9%)
Certifications per freelancer
8 (Germany: 4)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 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 Frankfurt 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 in Frankfurt 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 (100%)
- Professional Services (83%)
- Banking and Finance (67%)
- Transportation (67%)
- Media and Entertainment (50%)
- Advertising (33%)
- Energy (33%)
- Healthcare (33%)
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 raw warehouse data into reliable, reusable datasets with SQL. It applies software engineering practices such as modular models, version control, testing and documentation to analytics work. Teams use it to create trusted tables for reporting, forecasting, product analytics and operational decisions.
Core workflow
A dbt project describes how data moves from source tables to prepared models. Specialists define sources, write SQL models, set dependencies and run transformations inside the company’s cloud data warehouse. The resulting lineage makes upstream changes, downstream effects and ownership easier to understand.
- Build staging, intermediate and reporting models
- Add freshness, schema and data-quality tests
- Document models, columns and business definitions
- Manage environments with Git and pull requests
Ecosystem and tooling
dbt works with warehouses and query engines such as Snowflake, BigQuery, Databricks, Redshift and PostgreSQL. Its ecosystem includes dbt Core, dbt Cloud, packages, macros, seeds, snapshots and exposures. Strong specialists also work with orchestration tools, CI pipelines, semantic layers and catalog or observability products around the transformation workflow.
When expertise matters
Companies often bring in freelance dbt expertise when a warehouse is growing quickly, reporting logic is duplicated or teams cannot agree on trusted metrics. External specialists can establish project conventions, refactor fragile SQL and prepare a maintainable foundation for an analytics migration. In Frankfurt, collaboration may combine remote delivery with workshops for local data, finance or product teams.
- Replace scattered dashboard logic with governed models
- Migrate transformations from legacy ETL processes
- Improve test coverage, lineage and documentation
- Prepare dbt projects for CI and team handover
Skills to assess
Look for professionals who understand dimensional modelling, SQL performance, warehouse cost behaviour and data contracts, not only dbt syntax. They should be able to explain model grain, dependency choices and test coverage in business terms. Experience with Git workflows, orchestration, access controls and deployment practices is equally important for production work.
Signs of quality
A capable dbt specialist starts by clarifying source reliability, business definitions and expected consumers. They choose clear model layers, keep transformations reviewable and use tests that protect meaningful assumptions rather than creating noise. Good documentation, readable naming, incremental strategies where appropriate and a practical handover plan indicate work that can last beyond the engagement.
Frequently asked questions
Key details about dbt, drawn from the questions we get asked most.
dbt is used to transform raw data inside a warehouse into tested, documented and reusable models. Companies use it for analytics reporting, finance data, product metrics, forecasting inputs and other governed data products.
dbt focuses mainly on the transformation stage and runs SQL where the data already resides. Traditional ETL tools often combine extraction, loading and transformation in a visual workflow, while dbt emphasizes code review, modular models, lineage and automated tests.
A strong dbt specialist usually brings advanced SQL, dimensional modelling and experience with a cloud warehouse such as Snowflake, BigQuery or Databricks. Git, orchestration, CI, data quality, access management and dashboard requirements are also valuable.
The right level depends on the work. A focused model or testing improvement needs solid SQL and dbt practice, while a warehouse migration or project redesign calls for experience with architecture, deployment, performance and stakeholder alignment.
dbt is well suited to remote collaboration because projects are managed through code, pull requests, automated checks and shared documentation. Teams in Frankfurt can work remotely with specialists while scheduling focused sessions for requirements, metric definitions and handover.
A credible dbt portfolio should show clear model structure, meaningful tests, useful documentation and understandable lineage. Ask how the specialist handled changing sources, incremental models, warehouse performance and disagreements about business definitions.
dbt Core is the open-source command-line framework for developing and running dbt projects. dbt Cloud adds hosted development, scheduling, job management and collaboration features, so the choice depends on the team’s operating model and existing tooling.
A production-ready dbt model has a clear grain, stable dependencies, appropriate tests and documentation that reflects how the data is used. It should also have an intentional deployment process, monitored source freshness and a performance approach suited to the warehouse.
The average hourly rate of freelancers in Frankfurt, Germany who have used dbt in their recent projects is 110 €, which corresponds to a daily rate of about 883 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used dbt in their recent projects, 80% hold at least a Bachelor's degree, 60% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used dbt in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Frankfurt, Germany who have used dbt in their recent projects are German (100%), English (100%), and French (33%).
The most common industries among freelancers in Frankfurt, Germany who have used dbt in their recent projects are Information Technology (100%), Professional Services (83%), and Banking and Finance (67%).
The most common business areas among freelancers in Frankfurt, Germany who have used dbt in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (83%).
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
