dbt Experts in Berlin
for trusted analytics from over 15,000 CVs with the power of AIHire experts who turn raw warehouse data into tested, documented models, establish analytics engineering workflows, and connect dbt with modern data stacks. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Berlin, 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.
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
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.
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
Lasya M.
Last position:
Data Engineer at Carelon Global Solutions (Elevance Health)
- Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
- Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
- Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
- Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
- Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
- Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
- Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.
Filippo C.
Last position:
Sr. Analytics Engineer at Enpal
Metrify - OS & Analytics Layer Team:
- Built data architecture foundations through pre-commit contracts and modern dbt metadata structure
- Built and maintained modular layers for smart-meter rollout ops, codifying business rules into Star dwh.
Enpal - Central Data and Platform Team (SCM & Finance):
- Designed and built dbt models delivering a curated analytics layer for SCM and Finance stakeholders.
- Implemented inventory reconciliation across sources (ERP vs 3PL; snapshots vs movements) and surfaced variance drivers at SKU/location/channel level.
- Developed Weeks-of-Stock KPI and stock depletion projection (demand + inbound supply) to support planning and operational decisions.
Sander O.
Last position:
Interim Head of Contract Management at Enpal
- Directed the contracts management function for Europe's largest renewable energy portfolio, 10 FTE
- Implemented process automations by architecting scalable, data-driven workflows leveraging AI and traditional automation
Hamza K.
Last position:
Academic Research Contributor in Health Sector (Volunteer) at n/a
- Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
- Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.
Uditha W.
Last position:
Data Science Tutor at University of Europe for Applied Sciences
- Taught Python, Pandas, data analysis, visualization and Power BI to 250+ students.
- Guided practical projects from data preparation and exploratory analysis through visualization and dashboard creation.
- Explained complex analytical concepts clearly to audiences with different levels of technical experience.
Sejal V.
Last position:
Data & ML Engineering at Consulting
- Fractional leadership; consulting growth-stage startups and scale-ups on data strategy, ML products, and platform foundations
- Building decisioning systems for growth, personalization, & product experimentation, across e-Commerce, Digital Health, Energy, and Logistics
- Exploring Agentic AI & LLM-based tooling for production readiness patterns
Tobias L.
Last position:
Data Engineer at unitb consulting GmbH
Responsibilities: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.
Activities:
- Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
- Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
- Developed automated data pipelines with Python, dbt, and GCP services for various data sources
- Built monitoring and alerting systems for real-time platform monitoring
- Implemented data versioning and quality checks at every layer
- Designed automated testing and deployment pipelines in GitLab and Bitbucket
Achievements:
- Doubled production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
- Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, reducing configuration errors to 0
- Delivered a complete end-to-end data platform at ~10 €/month in infrastructure costs
- Migrated 7 database tables with 0 downstream issues
- Removed 100 % of exposed credentials, eliminating dependency on external vendors
- Delivered 3-team integration in 1 sprint
Discover over 15,000 top freelancers
Statistics of experts using dbt
Aggregated from the professional profiles of matched freelancers.
Experience
12 years (Germany: 14 years)
Position duration
2.2 years (Germany: 1.8 years)
Positions per freelancer
7 (Germany: 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
100% (Germany: 99%)
Master's degree or higher
63% (Germany: 68%)
Doctorate
10% (Germany: 9%)
Certifications per freelancer
3 (Germany: 4)
Most common languages
German, English, Spanish
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 Berlin 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 Berlin 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 (87%)
- Banking and Finance (48%)
- Professional Services (45%)
- Retail (45%)
- Education (35%)
- Energy (32%)
- Healthcare (29%)
- Automotive (26%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What dbt does
dbt is an open-source framework for transforming data inside a cloud or SQL-based data warehouse. It lets teams define transformations as modular SQL models, then manage dependencies, tests, documentation and deployment through a controlled workflow. The data stays in the warehouse while dbt makes its logic easier to review and maintain.
Core workflow
A dbt project typically turns raw source tables into staging models, intermediate logic and business-ready marts. Specialists configure sources, refs, snapshots, seeds, macros and exposures, then use version control and continuous integration to validate changes before release. This creates a clear lineage from source data to dashboards, reports and operational decisions.
Ecosystem and tooling
- Connect Snowflake, BigQuery, Databricks, Redshift or another supported warehouse
- Build reusable transformations with SQL and Jinja macros
- Add schema, data quality and freshness tests
- Publish documentation and lineage for analysts and stakeholders
- Run jobs through dbt Cloud, orchestration tools or CI pipelines
dbt commonly works alongside Airflow, Dagster, Fivetran, Looker, Tableau, Git and cloud data platforms. Strong specialists understand both the framework and the surrounding pipelines that move, schedule and consume the data.
When to hire expertise
Companies bring in freelance dbt expertise when a warehouse has grown difficult to trust, transformation logic is duplicated, or delivery needs stronger controls. A specialist can establish project conventions, refactor legacy SQL, migrate transformations from another tool and create a maintainable model structure. Berlin teams may also value professionals who can work remotely or on site and communicate clearly across English-speaking data and business groups.
Typical deliverables
- A structured dbt project with environments, packages and naming conventions
- Tested models for finance, marketing, product or operational reporting
- Source freshness checks, documentation and model ownership
- Incremental models and snapshots for changing historical data
- CI, deployment and monitoring workflows for reliable releases
The work may also include warehouse cost control, query optimisation, access coordination and handover documentation. The right scope depends on data volume, existing architecture and the maturity of the analytics team.
What strong specialists bring
Strong dbt professionals write readable SQL, understand dimensional modelling and know how warehouse behaviour affects performance. They distinguish a useful test from a noisy one, investigate lineage when results change and make assumptions visible in documentation. They also review pull requests carefully, collaborate with analysts and data platform teams, and leave behind conventions that others can follow. Experience with the relevant warehouse and orchestration setup matters as much as familiarity with dbt commands.
Frequently asked questions
Key details about dbt, drawn from the questions we get asked most.
dbt is used to transform raw warehouse data into reliable, documented datasets for reporting, analytics and decision-making. It focuses on the transformation layer, while separate tools usually handle ingestion, storage and dashboarding.
dbt performs transformations inside the target warehouse and treats SQL models as versioned project code. Traditional ETL tools may move and transform data in a separate processing layer, so the better choice depends on the warehouse architecture, team skills and governance needs.
A strong dbt specialist usually brings SQL, data modelling and warehouse expertise, plus practical knowledge of Git and testing. Experience with orchestration, ingestion tools, BI products and cloud platforms helps connect models to the wider data workflow.
A dbt freelancer can help with a focused migration, a new warehouse transformation layer or a broad project restructuring existing models. The required depth depends on source complexity, reporting needs, deployment controls and how much of the surrounding data stack is already established.
dbt is well suited to remote collaboration because projects are managed through Git, pull requests, automated checks and documented models. For Berlin-based teams, clear English communication may be important when specialists work across locations or coordinate with international stakeholders.
Teams often choose dbt when standalone SQL scripts have become hard to trace, test or deploy consistently. Its dependency graph, documentation, testing and environment workflows add structure without requiring the business logic to leave the warehouse.
Review whether dbt models are modular, readable, tested and documented, with clear lineage and sensible naming. Ask the specialist to explain handling for late-arriving data, changing schemas, incremental loads, failures and warehouse performance.
dbt refers to the transformation framework and its project workflow, while dbt Cloud is a hosted service that adds features such as job scheduling, deployment management and collaboration tools. A specialist should be able to work with the open-source command-line approach, the hosted service, or both, depending on the project.
The average hourly rate of freelancers in Berlin, Germany who have used dbt in their recent projects is 78 €, which corresponds to a daily rate of about 626 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used dbt in their recent projects, 100% hold at least a Bachelor's degree, 63% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Berlin, Germany who have used dbt in their recent projects have 12 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Berlin, Germany who have used dbt in their recent projects are German (100%), English (100%), and Spanish (13%).
The most common industries among freelancers in Berlin, Germany who have used dbt in their recent projects are Information Technology (87%), Banking and Finance (48%), and Professional Services (45%).
The most common business areas among freelancers in Berlin, Germany who have used dbt in their recent projects are Business Intelligence (94%), Information Technology (94%), and Product Development (65%).
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.
Munich 
Frankfurt Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
