
Data Warehouse Experts in Munich
matched in minutes from over 15,000 CVs with the power of AIHire experts who design scalable analytics architectures, develop reliable ELT pipelines and model data for reporting, forecasting and business intelligence. FRATCH quickly matches you with vetted, available freelancers who fit your technical needs.
Meet FRATCH Experts in Munich, who have recently used Data Warehouse
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management steering during a restructuring program (approx. 80 participants)
- Set up a PMO to ensure transparency, reporting and data-driven decisions
- Created an integration template to transfer team s...
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
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
Philip K.
Last position:
Consulting / Interim Management at self-employed
- Focus areas: restructuring, operations management, commercial management, purchasing, production
- Industries: automotive, metal processing, shipbuilding, electrical, elevators / escalators
Christiane N.
Last position:
Management Consultant at Christiane Neher Management Consulting
Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:
- Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
- Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
- Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
- Conceptual support for the development of an integrated reporting and performance management setup
- Execution of customer insights analyses to identify patterns and anomalies within customer data clusters
Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:
- Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
- Strategic-operational consulting for the introduction of RELEX including best practices
- Support in defining overarching goals and requirements (2-year target picture)
- Guidance in scoping a relevant supply chain network segment for the project
- Development of a roadmap for iterative, incremental RELEX setup and rollout
- Assessment of project dependencies (interfaces, configurations, etc.)
- Advice on prioritized implementation of business requirements and data interfaces
- Support in test planning (data validation, system testing, UAT)
- Consulting on internationalization, change management, training, and knowledge transfer
- Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX
Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:
- Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
- Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
- Proposal of quality improvements for program and modernization efforts
- Sparring partner and professional, technical, structural and organizational consulting for project and program management
Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:
- Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
- Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
- Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
- MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)
Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:
- Coaching of the core team with topic managers and team leads
- Introduction to the OKR topic and setup of the OKR cycle
- Establishment of the OKR approach in teams and on a cross-team level
Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:
- Analysis of current challenges
- Definition of overarching goals
- Development of a proposal for a new team structure
- Identification of required competencies, skills and responsibilities
- Advisory and alignment on communication and change management strategy
Emanuel F.
Last position:
Interim Architect & Data Taskforce at Freelancer / Project Assignments
- Data Engineering: Design and implementation of scalable data pipelines
- Legacy migrations to Microsoft Fabric (Lakehouse, Dataflows Gen2, Pipelines)
- BO Universe migrations to MS Fabric / Semantic Models / Power BI
- Taskforce for data-driven transformation projects involving Azure Fabric / Oracle / MSSQL
Kai P.
Last position:
Oracle Project Management and DBA at Scope Solutions AG
- Installation, maintenance and regular upgrade of the DB systems with 19x
- Use of OPatch and RU 19.27 on RHEL 8x, SLES 15.x and Windows
- DBA for DACH and European customers in production and last test environments (e.g. Konrad Adenauer) as well as others in CDB
- Processes via Confluence
- Support in operations for customers SR via Metalink
Any-Arlene N.
Last position:
Co-Founder · Data Engineering & Backend at zirikana (Kirundi Bible Web App) – Civic Technology
- Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
- Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
- Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
- Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.
Serge K.
Last position:
MLOps (machine learning operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Michael T.
Last position:
ETL Developer at Insurance service provider
DWH for customer and financial data
- Extension of the DWH with new data sources
- Report development
- Data quality management
Methodology: Scrum
Tools: Atlassian Confluence & Jira
Databases: Microsoft SQL Server
Programming languages: SQL, T-SQL
ETL: Microsoft SQL Server Integration Services (SSIS)
Frontend platform: PowerBI, Microsoft Reporting Services
Xinyang M.
Last position:
Sales Operations Analyst Intern at Capgemini
- Developed and maintained 5 Power BI dashboards for pipeline tracking, forecasting, revenue-gap, quota-achievement, and deal-performance analysis.
- Delivered weekly, monthly, and quarterly reporting used by approximately 100 stakeholders across Sales, Finance, and Marketing.
- Built semantic data models and ETL workflows using Power Query, DAX, and SQL; integrated Salesforce, SharePoint, internal data warehouse, and Excel sources.
- Automated data ingestion, cleaning, transformation, format standardization, KPI calculations, dashboard refresh, and reporting preparation using Power Query, DAX, and Power BI, eliminating several hours of recurring manual data preparation and reporting work.
- Standardized KPI calculations and built interactive reports with row-level security, drill-through, and Waterfall analysis for business reviews and forecasting.
Anitha N.
Last position:
Senior Data Engineer at Accenture GmbH
- Designed, developed, and configured scalable data applications aligned with business processes and technical requirements.
- Architected scalable, cost-effective data architectures leveraging Snowflake across AWS, Azure and GCP, integrating dbt for data transformation and modeling.
- Built and maintained robust ETL Data Pipelines, ensuring high data quality for seamless migration and cross-system integration.
- Demonstrated strong expertise in SQL & Python with extensive experience in data modeling, ETL/ELT pipeline development, and streaming data processing; proficient in Git-based version control, CI/CD practices, and testing frameworks, with solid knowledge of data quality, observability, cost optimization, security, and data governance principles.
- Led multiple data migration initiatives from SAP HANA to Snowflake using a modular dbt framework.
- Designed and maintained end-to-end data transformation workflows using dbt on Snowflake, implemented layered data models, optimized performance, and ensured high-quality data delivery for business intelligence and reporting.
- Managed development, QA, and production deployments through structured version control and release management using GitLab.
- Integrated and centralized data from multiple sources including relational databases, flat files, Excel, and large-scale systems into Snowflake.
- Applied strong expertise in Sales, Marketing, HR, and ERP data domains, developing and maintaining relevant KPIs and reporting solutions.
- Collaborated with cross-functional teams to deliver end-to-end data solutions on schedule through proactive issue resolution and effective coordination.
- Administered the Snowflake sandbox environment for Data Engineering division.
- Trained colleagues transitioning into data roles on Snowflake and provided technical guidance and mentorship to junior team members.
Hardeep B.
Last position:
Sr. Data Engineer at Charles Schwab Bank
- Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
- Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
- Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
- Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
- Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
- Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
- Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
- Created and maintained dashboards in Power BI to provide actionable insights.
Antonio D.
Last position:
Agile Project Manager at Openry GmbH
End Customer: Openry GmbH
E-commerce platform to globally commercialize high-quality Italian artistic productions. Several European shops are already operational and Asian markets soon coming up. My role as Agile Project Manager is to lead the complete team on both the customer and technical side (offshore) including strong strategic consulting, in a continuous delivery approach. As project in a small enterprise, the budget management aspects are particularly challenging, in a quest to deliver the maximum business value with minimal overheads. Technologies: Magento 2, M2E Pro, Linux, Apache, MySql, PHP (LAMP), Stripe
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
24 years (Germany: 22 years)

Position duration
3.7 years (Germany: 3.2 years)

Positions per freelancer
14 (Germany: 13)

Top business areas
Information Technology, Business Intelligence, Project Management

Top industries
Information Technology, Banking and Finance, Professional Services

Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
93% (Germany: 89%)
Master's degree or higher
68% (Germany: 57%)
Doctorate
15% (Germany: 10%)

Certifications per freelancer
2 (Germany: 3)

Most common languages
German, English, French

Speak two or more languages
95%
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 Munich 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.
Average rates of experts in Munich using Data Warehouse
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.
Data Warehouse 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 (82%)
- Banking and Finance (62%)
- Professional Services (62%)
- Automotive (49%)
- Insurance (44%)
- Manufacturing (44%)
- Retail (42%)
- Media and Entertainment (40%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a Data Warehouse Does
A data warehouse centralizes structured data from operational systems so teams can analyze it consistently. It separates analytical workloads from transactional applications and supports trusted reporting, dashboards, forecasting and strategic decisions. Strong designs define clear ownership, history and business meaning for every important data set.
Core Architecture
Projects may use cloud, on-premises or hybrid warehouse architectures. Specialists choose storage, compute, partitioning and workload patterns that suit data volume, query behavior, security needs and delivery speed. They also design dimensional models, data marts and semantic layers that make complex information usable across departments.
Ecosystem and Tooling
The work connects source systems, transformation frameworks, orchestration tools and business intelligence software. Common choices include Snowflake, Google BigQuery, Amazon Redshift, Microsoft Fabric, Azure Synapse Analytics and Databricks. Professionals may also work with dbt, Apache Airflow, SQL, Python, Kafka and catalog or observability tools.
- Integrate ERP, CRM, application and event data
- Build batch and near-real-time ingestion pipelines
- Model facts, dimensions, history and business metrics
- Add tests, lineage, monitoring and access controls
When Companies Need Specialists
Companies often bring in freelance expertise during a warehouse migration, a reporting transformation or a merger of fragmented data estates. External specialists can establish a target architecture, modernize legacy ETL, improve slow workloads or prepare the environment for self-service analytics. In Munich, collaboration may combine remote delivery with on-site workshops and communication in English or German.
What Strong Professionals Deliver
The best specialists connect technical design with business definitions. They document source-to-target mappings, challenge unclear requirements and create repeatable deployment processes. They understand data quality, privacy, role-based access, backup strategy and cost control, while keeping models understandable for analysts and decision-makers.
Choosing the Right Fit
Assess candidates through a concrete review of architecture decisions, pipeline design and production incidents they have handled. Ask how they validate reconciliations, manage schema changes, test transformations and measure warehouse reliability. The right professional can explain trade-offs between a traditional warehouse, a lakehouse and a data lake without forcing one pattern onto every use case.
Frequently asked questions
Quick answers to the questions that come up most around Data Warehouse.
A data warehouse combines information from operational sources for analysis and reporting. Companies use it for trusted dashboards, financial planning, customer analysis, supply-chain visibility and recurring business metrics.
A data warehouse usually emphasizes structured, governed data that is ready for SQL analysis. A data lake stores a broader range of raw files, while a lakehouse combines lake storage with warehouse-style management and querying. The right choice depends on data formats, governance, workloads and the skills available to the team.
A strong Data Warehouse specialist commonly brings advanced SQL, data modeling, ETL or ELT design and orchestration experience. Useful adjacent skills include Python, dbt, Apache Airflow, cloud storage, infrastructure automation, data quality testing, cataloging and business intelligence tools.
The right level depends on the scope, source complexity and operational risk. A data warehouse migration or redesign benefits from a professional who has handled production pipelines, legacy constraints, security and stakeholder alignment, not only prototype queries.
Yes, much of Data Warehouse work is suitable for remote collaboration because design, SQL development, testing and documentation are digital. On-site workshops can still help with source-system discovery, governance decisions and alignment with teams in Munich. Agree on working language, meeting routines and access procedures early.
Ask a Data Warehouse professional to explain a model, pipeline or migration they delivered and the trade-offs behind it. Look for clear thinking about grain, keys, history, testing, lineage, failure recovery and performance. A quality specialist can also connect technical choices to reliable business definitions.
A data warehouse can ingest ERP, CRM, finance, commerce, support, application and event data. Integration may use APIs, database replication, files, message streams or managed connectors. The specialist should define ownership, refresh expectations, schema handling and reconciliation for each source.
Before starting Data Warehouse work, clarify the business questions, source systems, security constraints, existing models, delivery milestones and ownership after handover. Also confirm the target cloud or on-premises environment, deployment process, data quality expectations and who approves metric definitions.
The average hourly rate of freelancers in Munich, Germany who have used Data Warehouse in their recent projects is 104 €, which corresponds to a daily rate of about 830 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Data Warehouse in their recent projects, 93% hold at least a Bachelor's degree, 68% hold at least a Master's degree, and 15% hold a doctorate.
On average, freelancers in Munich, Germany who have used Data Warehouse in their recent projects have 24 years of professional experience, with a single engagement typically lasting around 3.7 years.
The most common languages among freelancers in Munich, Germany who have used Data Warehouse in their recent projects are German (98%), English (93%), and French (20%).
The most common industries among freelancers in Munich, Germany who have used Data Warehouse in their recent projects are Information Technology (82%), Banking and Finance (62%), and Professional Services (62%).
The most common business areas among freelancers in Munich, Germany who have used Data Warehouse in their recent projects are Information Technology (96%), Business Intelligence (91%), and Project Management (67%).
Main locations of FRATCH Experts, who have recently used Data Warehouse
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.
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!

Berlin
Hamburg
Cologne
Frankfurt
Dusseldorf
Essen
Hanover
Nuremberg