Data Warehouse Expert
for trusted analytics, matched in minutes from over 15,000 CVsHire experts who design analytical data models, build reliable ETL and ELT pipelines, and deliver cloud data warehouse solutions across Snowflake, BigQuery, Redshift and Microsoft Fabric. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts who have recently used Data Warehouse
Fadi S.
Last position:
AI-Engineer at Recruitment Agency
- Design, development, and productive rollout of an Enterprise HR Copilot based on Microsoft Copilot Studio to automate internal HR processes
- Development of an AI-supported assistant for answering employee inquiries based on a SharePoint knowledge base and internal company HR documentation
- Integration of the Copilot into Microsoft Teams, including welcome logic, user guidance, and role-based routing
- Automation of HR processes and approval workflows with Microsoft Power Automate to reduce manual processing steps
- Development of realistic HR documents and response templates with Azure OpenAI, taking business requirements and consistent company policies into account
- Implementation of prompt strategies, knowledge management, and response optimization to improve response quality and user acceptance
- Close collaboration with business departments to analyze requirements and integrate the AI solution into existing company processes
Technologies:
Microsoft Copilot Studio, Microsoft Teams, Azure OpenAI, SharePoint, Power Automate, Power Platform, Microsoft 365, Prompt Engineering, Workflow Automation
Amit S.
Last position:
IT Project Manager – SAP S/4 HANA Delivery Consultant at CHG Meridian UK Limited
- Managed the integrated SAP S/4HANA delivery plan for 12 BTS workstreams, including milestone, dependency, and governance management.
- Coordinated end-to-end delivery across Business, IT, and Operations, focusing on execution, readiness, and issue resolution.
- Responsible for RAID, test, cutover, and deployment management to ensure a successful go-live.
- Implemented KPI tracking, status reporting, and PMO governance to provide transparent management of performance, risks, and escalations.
Martin R.
Last position:
TECH DUE DILIGENCE FOR PE, VC & FAMILY OFFICES (UNDER NDA) – AI STRATEGY at PE-, VC- & Family-Office-Portfoliounternehmen (vertraulich, unter NDA)
Two parallel workstreams: (1) Tech Due Diligence for acquisitions and portfolio companies. (2) AI strategy certification and AI governance consulting.
- Tech assessments for PE/VC acquisitions: code reviews, architecture analysis, scalability assessment
- Tech assessment frameworks and integration roadmaps for portfolio companies
- TÜV SÜD certification program: AI governance, EU Artificial Intelligence Act (EU AI Act)
- Strategic AI roadmap development for mid-sized companies
Results:
- Delivered several tech DD reports for investment decisions
- Developed integration roadmaps for portfolio companies
- TÜV SÜD “AI Strategy & Application Expert” (expected 31.12.2026)
Robert K.
Last position:
Interim Manager | Group Manager in the IT Operations & Digitalization division „Databases, Operations & Support" (DOS) at Landwirtschaftliche RentenBank
- Functional management and further development of a team of 28 IT employees (internal & external) in the areas of HelpDesk / HelpLine, RHEL (Red Hat), MUREX (trading system & applications), SAP basic operations
- Management of external service providers (including FI-TS for SAP basic operations)
- Personnel, resource and budget planning for the IT department and projects
- Introduction and establishment of regular communication formats (regular meetings, team and cross-departmental meetings)
- Ensuring application operations in a hybrid environment (Windows / Linux with database and web/application servers)
- Support for transformation projects to modernize the application landscape (e.g. DevOps approaches)
- Building and introducing digital IT procurement for hardware & software (e.g. with DELL)
- Development and management of the „IT Operations DOS" department based on the company strategy
- Preparation of management reports & decision papers on IT projects, optimization potential and automation opportunities
- Representing the department in Rentenbank committees and ensuring regulatory compliance (BaFin §44, DSGVO, BSI, MaRisk)
Bruno P.
Last position:
Product Owner
Design and implementation of a „unified-commerce“ platform for SMEs to sell and deliver multi-product bundles
Achievements: On-time design, delivery and customer acceptance of a 100% functional, CPQ-based „buy flow“ process for configuring and selling multi-product bundles within the specified timeframe of 90 days. Successfully tested integration of various interface services for the areas of: customer search, enrichment of customer data, address validation, service qualification, phone number validation, credit check, appointment selection and Quote-to-Order Transition.
Responsibilities:
- Strategic goal implementation: Derivation and implementation of strategic customer goals (e.g. release content, business value).
- Backlog Management: Creation and elaboration of backlog items (Initiatives, Epics, User Stories, Defects) in close coordination with the project team and customer.
- Prioritisation & Releases: Responsibility for prioritising the Product Backlog and implementing defined release goals.
- Deliverable Tracking: Tracking work results on the supplier and customer sides.
- Roadmap & Release Planning: Development and implementation of roadmaps and release plans together with the customer.
- Scope Responsibility: Responsibility for the contractually agreed scope of services.
- Claim Management: Active claim and change management towards the customer.
- Team Coordination: Management and coordination of the development team.
- Use of Synergies: Use of synergies between customer projects and product development.
- Proposal Preparation: Preparation of proposals (with supervision) and presentations on site at customer and partner locations.
Skills: Development, communication and implementation of product visions; Product Backlog Management; Stakeholder Management; Regular reporting to management and Steering Committees; Requirements analysis & Engineering; Conducting and documenting workshops; Functional leadership and coordination of (distributed) project teams and external service providers; Epic Management; User Story specifications; Creation of Use Cases, support with software testing and User Acceptance Testing (UAT); Release Management and Sprint Planning; Design of TO-BE processes; Process optimisation; Planning, design and specification of interfaces to existing and new systems; Identification, assessment and management of project risks; Active claim and change management; Facilitation of Sprint Planning and Reviews; Data migration; Scrum; Kanban; REST API; JSON; XML; BPMN; UML; Jira; Confluence
Ebru A.
Last position:
Product Analytics & App Tracking Consultant at EnBW mobility+ AG & Co. KG
- Product Analytics, Mobile App Tracking & Tracking Governance (B2C Mobility App) – agile project management (Scrum/Kanban)
- Product Ownership for Product Analytics and Mobile App Tracking of the EnBW mobility+ app; gathering, prioritizing, and translating business requirements into actionable concepts and Azure DevOps user stories with acceptance criteria.
- Derivation of tracking requirements when introducing new app features (including Resilient Map), definition of tracking parameters (screens, events, custom definitions), and ensuring privacy-compliant tracking (Firebase, GA4, Adjust) based on the tracking concept.
- Design and adaptation of dashboards and funnel reporting for campaigns (GA4 validation, onboarding and order flow analyses, conversion funnels, charging start flow) to identify drop-off points and optimization potential.
- Management of the technical raw data export (Adjust to BigQuery) and connection to the data warehouse/data lakehouse, including data mapping; collaboration with international development teams, Data Engineering, Marketing/Sales, and Product Management.
- Establishment of standardized tracking architecture, naming conventions, and governance; analysis and expansion of tracking (new features and “blind spots”), test design, handover to testers, and quality assurance and approval before releases; documentation in Conceptboard.
Wolfgang O.
Last position:
Project Manager at EnBW - Netze Südwest
- New development and further development of the existing MS Dynamics CRM
IT systems: Microsoft Dynamics Customer Service, SharePoint, DevOps, SAP IS-U
- CRM implementation / further development
- Taking over from the previous service provider
- Business process analysis
- Agile project organization
- Business analysis / requirements engineering with AI support
- Use of AI in development
- Analysis of master data processes
- CRM customer data management
- Requirements documentation
- Stakeholder management
- Workshop moderation
Stefan O.
Last position:
Founder at ProtocolEngine.io
Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.
- Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
- Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
- Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
- Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
- Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
- Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.
Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.
Eric B.
Last position:
Quality Assurance Manager (QSV) at Federal Employment Agency
Supporting the International Web Presence of the BA (IntWeb) project in the area of quality management, with the aim of taking responsibility for the quality of processes and project results while considering BA standards. The main objectives of the project are to give professionals abroad a quick overview of their opportunities for moving to Germany and to enable them to take the necessary steps consistently and with digital support by providing access to services.
Defining the general guidelines in the QA handbook
Summarising test results in QA reports for PLA
Analysing project results for improvement opportunities
Quality management of requirements analysis (particularly processes, methods, and tools)
Ensuring compliance with SERA requirements
Creating a cross-project test concept
Agreeing on sprint completion reports
Formal review of work results in accordance with requirements and/or the project plan
Contact person for internal audit, external audits by auditors, or BRH (Federal Court of Audit)
Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes
Michael S.
Last position:
Establishment of Compliance/TPRM at Haftpflichtkasse
Establishment of Compliance Department & DORA Operationalization
- Establishment of a complete compliance organization in accordance with DORA
- Development and operationalization of the SfO
- Use of AI agents for automation:
- Evaluation of due diligence questionnaires including risk classification
- AI-supported contract analysis (DORA/MaRisk compliance)
- Monitoring of external data sources (cyber incidents, newsfeeds)
- Establishment of a decentralized risk and action register
- Preparation of GAP analyses and derivation of measures
- Establishment and maintenance of the Outsourcing Information Register
- Use of proprietary TPRM frameworks, checklists and process models
Establishment of Compliance Department & DORA Operationalization
- Establishment of a complete compliance organization in accordance with DORA
- Development and operationalization of the SfO
- Use of AI agents for automation:
- Evaluation of due diligence questionnaires including risk classification
- AI-supported contract analysis (DORA/MaRisk compliance)
- Monitoring of external data sources (cyber incidents, newsfeeds)
- Establishment of a decentralized risk and action register
- Preparation of GAP analyses and derivation of measures
- Establishment and maintenance of the Outsourcing Information Register
- Use of proprietary TPRM frameworks, checklists and process models
- Project controlling - presentation and structured measurement of project goals achieved as part of management reporting.
- Overall responsibility for establishing a Compliance, Governance and Risk organization
- Establishment of an integrated GRC model and executive reporting for the Management Board.
Hans-Dieter G.
Last position:
Training as an AI Expert
I continuously expand my expertise in AI and automation. I work with ChatGPT, OpenAI, Manus, Gemini, MS CoPilot, APIs, LangChain, Hugging Face, Manus, TensorFlow, and Auto-GPT, as well as Python-based ML frameworks and MLOps tools, to intelligently transform traditional software development, analysis, and testing processes.
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
Karin A.
Last position:
AI Benchmark Engineer | Native language specialist German at Lilt
- Task Engineering: Evaluating Coding Agents.
- Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
- Prompting & Translation: finding failure points where AI does not work, in German.
- Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
- Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
- Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
- Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.
Songül D.
Last position:
Freelance SAP BW Consultant at DKV Mobility Services
- Designed and implemented enhancements in SAP BW on HANA 7.5 in the context of CRM migration and S/4HANA and BW/4HANA transformation programs
- Migrated SAPI data sources to the ODP framework as part of the S/4HANA migration
- Delivered SAP ECC data to Snowflake using BW data models and Calculation Views for Power BI analytics
- Integrated SAP and non-SAP data sources (including MS Dynamics)
- Improved reporting transparency through consolidated data models
- Optimized data loading processes for FI-CO data sources, significantly improving load times and system performance
Florian B.
Last position:
Project Management / PMO Consultant
PMO & Project Organization Blueprint for Restructuring
Renewable Energy / Solar Equipment
Technologies / Methods: PMO setup, KPI tracking, project organization, Jira, Confluence
- Developed measures to improve management control during a restruct...
Discover over 15,000 top freelancers
Statistics of experts using Data Warehouse
Aggregated from the professional profiles of matched freelancers.
Experience
22 years
Position duration
3.2 years
Positions per freelancer
13
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
89%
Master's degree or higher
57%
Doctorate
10%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
95%
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 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 16 Oct 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 (85%)
- Banking and Finance (58%)
- Professional Services (50%)
- Manufacturing (37%)
- Insurance (35%)
- Automotive (35%)
- Retail (34%)
- Healthcare (32%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Foundations
A data warehouse centralizes structured information from operational systems so companies can analyze performance, customers, finance and operations from a consistent source. It separates analytical workloads from transactional databases and supports governed reporting, dashboards and business intelligence.
Data Pipelines
Specialists connect applications, databases, APIs and files through ETL or ELT pipelines. They clean, validate and transform data before loading it into an enterprise data warehouse or cloud data warehouse. Strong delivery includes scheduling, retries, lineage, monitoring and clear ownership of failed loads.
Models And Tools
Modern warehouse work spans dimensional modeling, star schemas, data marts and semantic layers. Common ecosystems include Snowflake, Google BigQuery, Amazon Redshift, Microsoft Fabric, Azure Synapse Analytics and Databricks SQL. Professionals may also use dbt, Airflow, Fivetran, Matillion, SQL and Python.
Where It Helps
Companies bring in freelance expertise when reporting is slow, source systems disagree or a migration needs careful control.
- Consolidating finance, sales and customer data
- Moving from on-premises systems to cloud warehouses
- Creating trusted metrics for BI and executive reporting
- Improving pipeline reliability, cost control and query performance
Project Signals
A company usually needs specialist support when teams maintain conflicting spreadsheets, analysts cannot trace a metric back to its source, or dashboards depend on manual exports. Freelance professionals can assess the current architecture, define a migration path and leave documentation that internal teams can maintain.
Quality Markers
Strong professionals ask how data is produced, used and governed before choosing a warehouse pattern. They test transformations, protect sensitive fields, monitor freshness and explain trade-offs between cost, speed, flexibility and control. Look for practical evidence of reliable models, recoverable pipelines and clear communication with analysts and business stakeholders.
Frequently asked questions
Before you brief your next project: the most common questions about Data Warehouse.
A data warehouse stores prepared data from multiple operational systems for analysis and reporting. Companies use it for dashboards, financial reporting, customer analysis, forecasting and consistent business metrics.
A data warehouse usually stores structured, modeled data that is ready for governed analysis. A data lake can hold raw structured, semi-structured and unstructured information, while a lakehouse combines parts of both approaches.
A strong data warehouse specialist may work with Snowflake, BigQuery, Amazon Redshift, Microsoft Fabric, Azure Synapse Analytics or Databricks SQL. Useful adjacent skills include SQL, Python, dbt, Airflow, cloud security, data quality and business intelligence tools.
The right data warehouse professional depends on the project scope, source complexity and governance requirements. A focused reporting model may need a different profile from a migration involving many systems, sensitive data and demanding service levels.
Yes, much data warehouse work can be delivered remotely through cloud access, version control, documentation and regular planning sessions. On-site collaboration can still help when source systems are difficult to access or business teams need close workshops.
Review how the data warehouse professional handles data modeling, testing, lineage, monitoring and documentation. Ask for examples of resolving inconsistent source data and improving reliability without hiding important trade-offs.
An enterprise data warehouse is useful when multiple departments need shared definitions, governed access and dependable cross-functional reporting. It is less suitable as a default repository for every raw file or exploratory dataset.
Before starting data warehouse work, clarify source systems, data owners, reporting goals, security rules, refresh expectations and acceptance criteria. A clear discovery phase also exposes undocumented transformations and prevents teams from rebuilding inconsistent metrics.
The average hourly rate of freelancers who have used Data Warehouse in their recent projects is 104 €, which corresponds to a daily rate of about 834 € based on an 8-hour working day.
Of the freelancers who have used Data Warehouse in their recent projects, 89% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers who have used Data Warehouse in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 3.2 years.
The most common languages among freelancers who have used Data Warehouse in their recent projects are German (99%), English (95%), and French (21%).
The most common industries among freelancers who have used Data Warehouse in their recent projects are Information Technology (85%), Banking and Finance (58%), and Professional Services (50%).
The most common business areas among freelancers who have used Data Warehouse in their recent projects are Information Technology (98%), Business Intelligence (85%), and Project Management (73%).
Main locations of FRATCH Experts, who have recently used Data Warehouse
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Dusseldorf 
Dortmund 
Essen 
Hanover 
Nuremberg 
Vienna 
Zurich Countries:
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FRATCH CEO
