Data Warehouse Experts in Frankfurt
in minutes from over 15,000 CVs with the power of AI.Hire experts who design data warehouse layers, build reliable ELT pipelines, and shape reporting models for finance, operations, and analytics teams. They work with Snowflake, BigQuery, Redshift, SQL Server, and classic on-premise warehouse stacks. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Frankfurt, who have recently used Data Warehouse
Umut Gülac
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Justina Kmiecik
Last position:
Freelance Consultant for Change & Data Transformation at Freelance Fast Data Consulting
Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present
- Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
- Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.
Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025
- Concept development and solution design for new end-to-end processes including technical interfaces
- Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
- Analysis and validation of data models
- Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
- Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
- Documentation and comments on technical and business requirements to support implementation in agile squads
Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present
- Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
- Development of business solution concepts for migration to the target system, including system integration and data flows
- Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
- Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
- Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.
Monika Thepale
Last position:
Senior ETL Lead at Takeda GmbH
- Led design, development, and deployment of data solutions supporting a major pharma acquisition for Takeda Pharmaceutical Company, delivering transparency reporting systems across Azure,Databricks (Python and Shell Scripting) platforms.
- Owned,Designed and developed scalable ELT pipelines to process Customer and Product data using Azure, complex SQL, Databricks, and shell scripting, enabling efficient data integration and processing across multiple sources including job orchestration and workflow automation.
- Implemented performance optimization techniques (query tuning, parallelism, workload optimization), improving system efficiency and processing time.
- Applied strong analytical and problem-solving skills to assess technical solutions and support business requirements for compliance and transparency reporting.
- Designed scalable data foundations suitable for downstream analytics and AI workloads.
- Led data quality initiatives by assessing multiple source data, defining quality metrics, and establishing processes for monitoring and continuous improvement.
Tan Pham
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Mustafa Kederoglu
Last position:
Senior Network Design and Engineer at Helaba
Designed and specified the technical network integration of a new business-critical application system (MUREX) in the capital markets area in a complex interface and outsourcing environment.
Created component specifications, a catalog of measures and an implementation plan.
Ensured proper integration of the developed results in line with the bank’s framework: IT compliance, IT security, change and release management.
Selected and integrated a new service provider for the bank; moved critical bank applications to the provider.
Designed, implemented and supported the new Cisco network and Fortinet security setup at the service provider data center.
Acted as technical interface between the bank, service providers and consulting partners.
Supported and further developed the network and security infrastructure (clients, servers, networks); performed error analysis and implemented solutions within agreed service levels.
Analyzed and diagnosed all security and network failures, glitches and malfunctions.
Initiated continuous improvements to ensure efficient resource use and acceptable response times for users.
Provided network support in a financial services organization and prepared operational changes on production banking network infrastructure for both large and small projects within strict change management discipline.
Designed, defined, tested, governed and improved engineering standards.
Performed the role of network architect for medium to large projects involving team resources.
Judith Beyrle
Last position:
BI & Analytics Consulting
- Analysis of web and campaign performance to derive actionable insights for marketing and growth optimization
- Implementation and maintenance of tag management solutions to ensure reliable and consistent data collection
- Continuous development and optimization of reporting structures with a focus on scalability and data quality
- Conducting regular deep-dive analyses and leading monthly stakeholder sessions to present findings and align on optimization measures
- Designing and managing end-to-end data flows from data collection to visualization
- Tools: GA4, Google Tag Manager, Looker Studio, Airbyte, BigQuery
Eric Bouendeu
Last position:
Quality Assurance Lead (QSV) at Federal Employment Agency
Supported the International Web Presence project of the Federal Employment Agency (IntWeb) in quality management, taking on responsibility for the quality of processes and project deliverables while adhering to BA standards. The project's main goals are to give professionals abroad a quick overview of their chances to move to Germany and to enable them to take the necessary steps in a consistently digital way.
Set the fundamental guidelines using the QA handbook
Summarized test results in QA reports for PLA
Analyzed project outcomes for improvement opportunities
Quality management of requirements analysis (especially processes, methods and tools)
Ensured compliance with SERA guidelines
Created a cross-project test concept
Agreed on sprint completion reports
Conducted formal reviews of deliverables according to guidelines and/or project plan
Acted as contact person for internal audit and external audits by auditors or the Federal Audit Office (BRH)
Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes
Ulm Paunel
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.
Werner Keil
Last position:
Test Coordinator, Designer and Engineer at IBM
- Testing the SekIDP and related components
- Test design, execution and automation, microservices, GitHub Enterprise, Eclipse, Katalon Test Platform, API Testing, Confluence 8, JIRA/Xray, Draw.io, Swagger/OpenAPI, Postman, Docker, Kubernetes, Podman, PuTTY, E-Health, Telematik, Gematik standards, EPA, E-Rezept, sektoraler IDP, encryption, XaDES, PaDES, DICOM, HL7, FHIR, IHE, ICD, SSO, SAML/Shibboleth, OAuth, smartcards, JWT, two factor authentication Android and iOS, Wireshark, BrowserStack, Cypress, gRPC, REST, SOAP, WS-Security, Linux Shell, PowerShell, SSH/SSL, Java, Kotlin, Cordova, Gradle, Groovy, Python, TypeScript
Waleri Moretz
Last position:
Project Manager at WAMOCON Academy
- Project planning and resource planning
- Requirements definition and technology selection
- Data migration and risk management
- Monitoring up to go-live
- Tools: Office365, Jira XRAY, Strato, Onboarding App
Jakub Szepietowski
Last position:
Oracle Consultant at Airline Sector
- Microsoft Azure: design, sizing, and capacity analysis including PoC
- Microsoft Azure: final implementation for migration from on-prem RAC to single instance Data Guard
- Performance tuning and troubleshooting for crew management systems (pilots and briefings)
- Design and implementation of a disaster recovery-aware system based on RAC Extended Cluster and Data Guard
- OEM: Oracle Cloud Control maintenance, installation and upgrades (12.1.0.5 > 13.3 > 13.5)
- OEM: creating an agent golden image with new RU and security fixes for a full-scale environment
- OEM agent upgrade
- OEM: developing custom metric extensions and reports
- OEM: full monitoring setup with template collection and monitoring templates and incident rule configuration
- Upgrades: GI from 11.2.0.4 to 12.1.0.2, to 18.4, to 19.6+
- Upgrades: databases from 11.2.0.2 to 12.1.0.2, to 19.18+
- Redesign and license optimization based on Oracle SE on ODA and DBVisit
- Design of a virtualized platform based on OLVM and license optimization using hard partitioning
- Migration of databases from bare metal to OLVM
Peter Weileder
Last position:
ISO 27001 Auditor for health insurance archive system at Health insurance company
The replacement of the existing archive system (document management system – DMS) on a host-based platform is well advanced.
The internal audit is meant to ensure the company's quality standards.
GDPR
ISO 27001 ff.
BSI
DORA
Patient data regulations
Host / Cloud / S3 / Container / highly scalable / Nuxeo
Budget: 50,000
Team: 1
Kamran Virk
Last position:
Agile Delivery Manager at Sparecodes Incorporation
- Highly successful role as lead data analytics expert at a US consulting startup.
- Managed stakeholder expectations by ensuring team delivery velocity using Agile and Lean practices.
- Trained and assembled international offshore data science teams of DevOps engineers, BI developers, and technical support specialists.
- As Sparecodes' data analytics experts, we improved our clients’ business outcomes through requirements management, dashboard and report development, migration, automation, and production support using IBM Cognos, AWS, SAP, Oracle, Teradata, CRM, ERP, Confluence, and Microsoft.
- Provided effective coaching and mentoring for international, multicultural teams in a remote environment, covering new tools and techniques, Agile best practices, internal and external communication, and presentation skills.
- Coordinated technical processes efficiently, including managing and implementing project changes and control processes.
- Promoted strong team engagement and supported employees’ career development, including business change management through coaching.
- Enhanced project status reports by providing insights into team productivity, predictability, and backlog burn-down, leading to improved project outcomes.
- Successfully led the coordination and implementation of software solutions for clients in mechanical engineering, including automation system integration and customization to meet client needs.
Marie-Josée Mache
Last position:
Java Engineer / Developer at Davaso GmbH
- Involved in the full development lifecycle, including design, coding, testing, and deployment of Java-based applications.
- Built and maintained high-performance RESTful APIs and microservices, ensuring scalability and reliable data exchange.
- Practiced code reviews, used version control systems (e.g., Git), and collaborated closely with cross-functional teams to deliver robust software solutions.
- Implemented, managed, and optimized complex business logic and decision-making processes using the Drools Rules Engine, leveraging DRL (Drools Rule Language) for dynamic configuration.
- Developed software solutions for a major service provider in the healthcare insurance sector, specifically focusing on claims processing and reconciliation logic to ensure cost-effective reimbursement for health funds.
Kabir Khaleque
Last position:
AI Engineer / Banking IT Specialist at Hamburg Commercial Bank (HCOB) & Real Estate Firm
- Developed a retrieval-augmented generation (RAG) application using LangChain and LangGraph for corporate document parsing, delivered as an installable Electron desktop application with local AI models via Ollama.
- Currently providing ongoing AI feature support for the Loan Pricing Tool at Hamburg Commercial Bank, with a commitment of three days per month.
- Architected Kubernetes-native solutions, including Helm chart configuration and Azure DevOps pipeline integration.
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
19 years (Germany: 22 years)
Position duration
2.4 years (Germany: 3.3 years)
Positions per freelancer
13
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Banking and Finance, Information Technology, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
83% (Germany: 88%)
Master's degree or higher
48% (Germany: 57%)
Doctorate
7% (Germany: 10%)
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 95%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Frankfurt 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 Frankfurt 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it covers
A data warehouse brings data from many systems into one place for reporting, analysis, and planning. It is built for clean history, stable definitions, and fast access to trusted data. Teams use it for dashboards, finance views, customer analysis, and operational reporting.
Common stacks
- Snowflake, BigQuery, Amazon Redshift, Azure Synapse
- SQL, ELT, dbt, and orchestration tools such as Airflow
- Dimensional models, star schemas, and data marts
- BI layers for Power BI, Tableau, and Looker
When to bring in help
Companies hire freelance specialists when warehouse loads are slow, data definitions conflict, or reporting breaks after source changes. They also step in during cloud migrations, platform redesigns, or when a Frankfurt team needs short-term support for a finance or analytics rollout. Strong work is clear, structured, and easy to maintain.
Delivery work
A strong expert can define source-to-target mappings, model facts and dimensions, tune SQL, and stabilize pipelines. They also handle testing, documentation, and access patterns so analysts can trust the numbers. In Frankfurt, this often matters for groups that need close work with business teams in German and English.
What good experts do
- Keep business logic consistent across reports
- Reduce duplicate data and unclear ownership
- Design for auditability and traceable changes
- Balance performance, cost, and maintainability
- Work well with analysts, engineers, and stakeholders
Related skills
Data warehouse work often sits next to ETL and ELT design, SQL optimization, data modeling, cloud storage, and BI integration. Many projects also need source system analysis, governance, data quality checks, and release coordination. The best freelancers explain trade-offs plainly and document decisions well.
Frequently asked questions
What clients ask us most about Data Warehouse — answered in short.
A strong Data Warehouse is used to combine data from sales, finance, operations, and product systems into one reliable reporting layer. It supports dashboards, historical analysis, and controlled metrics that teams can trust. Companies bring in specialists when they need one source of truth instead of many disconnected reports.
A Data Warehouse stores curated, modeled data that is ready for analysis and business reporting. A data lake is usually broader and holds raw or semi-structured data with less upfront modeling. Many modern teams use both, but the warehouse is still the place for trusted metrics and consistent definitions.
A good Data Warehouse specialist often works with Snowflake, BigQuery, Amazon Redshift, Azure Synapse, SQL, dbt, and Airflow. For reporting, knowledge of Power BI, Tableau, or Looker is useful. The exact stack matters less than the ability to model data cleanly and keep pipelines stable.
A strong Data Warehouse professional usually brings SQL tuning, data modeling, ELT design, and testing discipline. Experience with source systems, cloud storage, governance, and BI tools helps a lot too. Clear documentation is important because warehouse work is often shared across analytics and business teams.
A Data Warehouse project needs more than basic SQL if the data model, pipeline logic, or reporting rules are important to the business. Small fixes can be handled by a lighter profile, but migrations, redesigns, and performance work need someone who has done the same type of work before. The hardest part is usually not loading data, but keeping definitions consistent.
Yes. Data Warehouse work is often done remotely because most tasks happen in SQL, modeling tools, and cloud consoles. In Frankfurt, on-site time can still help when the project needs close alignment with finance, compliance, or German-speaking stakeholders, but many delivery steps fit well in a remote setup.
Look for a Data Warehouse specialist who can explain the model, the source-to-target flow, and the business meaning of each field. Good work is easy to test, documented, and resilient to source changes. A clear sign of quality is when the person talks about data correctness, lineage, and maintainability before talking about tools.
In a Data Warehouse setup, the warehouse is the central curated data store, data marts serve specific teams or domains, and the BI layer turns the modeled data into reports and dashboards. A good specialist knows where each layer belongs and avoids pushing business logic into the wrong place. That keeps reporting faster and easier to maintain.
The average hourly rate of freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects is 104 €, which corresponds to a daily rate of about 831 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects, 83% hold at least a Bachelor's degree, 48% hold at least a Master's degree, and 7% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects are German (100%), English (97%), and French (23%).
The most common industries among freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects are Banking and Finance (74%), Information Technology (71%), and Professional Services (43%).
The most common business areas among freelancers in Frankfurt, Germany who have used Data Warehouse in their recent projects are Information Technology (100%), Business Intelligence (83%), and Project Management (71%).
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.
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