Azure SQL Database Experts in Germany
in minutes from over 15,000 CVs with the power of AI.Hire experts who design, tune, and support Azure SQL Database solutions for transactional apps, reporting layers, and cloud migrations. They handle elastic pools, security, backups, and performance troubleshooting, matched fast and precisely with vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Azure SQL Database
Fadi Shoaa
Last position:
Development of a production-ready Enterprise Document AI & Recommendation Platform at Freelancer
- Development of a production-ready Enterprise AI solution for the automated processing of invoices and business documents
- Integration of Azure AI Document Intelligence and LLM technologies into existing business processes
- Development of robust REST APIs for automated document processing and system integration
- Extraction, validation, and storage of structured invoice data in Azure SQL as a base for analytics and machine learning models
- Development of an AI-based recommendation engine with machine learning and deep learning to generate personalized product recommendations based on historical purchase data
- Implementation of logging, monitoring, error handling, and validation mechanisms for stable production use
- Collaboration with business teams to define business rules and integrate the solution into existing enterprise processes
Technologies: Python, Azure AI Document Intelligence, Azure OpenAI, Azure SQL Database, REST APIs, Machine Learning, Deep Learning, OCR, Pandas, JSON, Workflow Automation
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.
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Alexander Bromberg
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Nisanthan Sivarajah
Last position:
Business Intelligence Consultant (freelance) at NBIC – Nisanthan BI Consulting
Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)
5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models
Proposal and feasibility assessments for BI and reporting projects
Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development
Custom ERP system
Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.
Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.
Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.
Timesheet app
Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.
Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.
Cash-flow modelling
Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.
Implementation: Built and extended the CF model to include project-development cash flows.
Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.
Hoa Josef Nguyen
Last position:
AI Architect and Enabler at Inhouse / AI Business
Technologies: n8n, Notion, OpenAI API, Claude, MS AI Foundry, MS CoPilot Studio, MS CoPilot, LLM, Node.js, Vercel, LangGraph, PostgreSQL, pgEdge, pgvector, Docker, LangChain, Ollama, Open WebUI
- Continuous evaluation and prioritization of internal automation needs
- ~20 AI agents in active use: research, content pipelines, document processing
- 5 n8n workflows for automated data and process control
- Architecture built on the same principles as in customer projects: state management, event-driven orchestration, API integration
- Ongoing operation and further development
Any-Arlene Niyubahwe
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.
Tobias Lewen
Last position:
Data Engineer at unitb consulting GmbH
Tasks: 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 different data sources
- Built monitoring and alerting systems for real-time platform monitoring
- Implemented data versioning and quality checks at every layer
- Designed automated test and deployment pipelines in GitLab and Bitbucket
Achievements:
- 2× 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, configuration errors to 0
- Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
- Migrated 7 database tables with 0 downstream issues
- Removed 100% exposed credentials, eliminated external vendor dependency
- Delivered integration of 3 teams in 1 sprint
Mario Techera
Last position:
Project Lead/Manager / Consultant at all-BI GmbH
- Establishing the Microsoft Fabric platform with the company as the central data warehouse and reporting system.
- The company migrated several operational systems including D365 to new version. The new data warehouse is based on a Fabric/Power BI architecture with Azure cloud Entra Authentication.
Tasks Performed:
- Full administrative responsibility for the Fabric platform F64 and F32 capacities, as well as two F8 capacities for development and prototyping.
- Integration of Fabric with Microsoft Entra.
- Data modeling for the data warehouse bronze, silver and gold layers using data modeling tools.
- Star Schema as well as entity relationship modeling.
- Data modeling for data marts and for dimensional modeling and Power BI (semantic model).
- Design of data models for Microsoft SSAS multidimensional and tabular OLAP cubes using DAX and MDX.
- Definition of design patterns for the ETL team for loading OLAP cubes (Tabular and MD), star schemas and data vault structures.
- Planning and managing team of 4 ETL and reporting developers.
- Performance Tuning of Power BI reports, particularly the semantic layer, as well as the Fabric notebooks
- SQL Performance Tuning.
- DB Design for Azure SQL.
- Reporting directly to project senior management.
Label: Power BI, Fabric, Analysis Services (multidimensional and tabular), D365, SSIS, Tabular Editor, SQL Server and Azure SQL, TOAD Data Modeler, DBSchema, Visual Studio Code, DAX Studio, SSMS, Visual Studio, Jira and Confluence.
Cedric Oettel
Last position:
Development at Construction industry
- New development of project room functions
- Connection of REST API of a self-developed web service (.NET 7/8) as Azure App Service
- UI tests with Playwright
- Extension of Azure DevOps pipelines
- Migration to Azure SQL Server
- Software / technology: SharePoint Online, PowerShell scripts, SharePoint Framework, MobX, C#, Logic Apps, Playwright, Azure SQL Server, Graph API
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.
Thomas Grevenkamp
Last position:
Senior .NET / Cloud Engineer at Freelance
Building an observability and alerting solution for Business Central Job Queue monitoring
- Built a central monitoring solution to track the Business Central Job Queue in a multi-organization environment in Azure DevOps
- Integrated Azure Application Insights and Log Analytics for structured collection and analysis of job runtimes and error events
- Developed KQL queries for targeted analysis of failed jobs and detection of error patterns
- Connected Grafana and Power BI to visualize operational metrics and job status in real time
- Implemented an automated alerting workflow with Power Automate – when a job fails, a notification email is sent immediately
- Ensured transparency about the state of productive background processes during live operations
Result: Full transparency over failed Business Central jobs · Clear reduction in response time through automated email alerting · Stable foundation for proactive operation of productive background processes
Technologies: Azure DevOps | Application Insights | Log Analytics | KQL | Grafana | Power Automate | Power BI | Business Central | Azure Monitor
Alexander Kapincev
Last position:
Senior Fullstack Developer at Deutsche Vermögensberatung AG (DVAG)
- Further development and maintenance of a complex sales platform focused on digital closing processes, customer portal interactions, and document generation for financial and insurance products
- Development and maintenance of microservices with Spring Boot 3 and Kotlin
- Frontend development with Angular 20 to display products, applications, and documents
- Conducting end-to-end tests with Playwright and integration tests with WireMock
- Creating and optimizing Quartz jobs and CronJobs
- Refactoring the security configuration in a multi-realm Keycloak setup with custom FilterChain, permission evaluator, and factory routing
- Creating dynamic emails with Thymeleaf
- Extensive error analysis with Application Insights, Log Analytics, and direct SQL debugging
- Introducing a dynamically controllable security architecture with flexible token processing based on path and realm
- Stabilizing and clearly structuring the closing process for complex product models
- Significantly increased maintainability and readability of code through modular refactorings
- Improved test stability and depth by combining Playwright, WireMock, and integration tests
- Targeted performance optimization through analysis of Hibernate statistics, query tuning, and use of SQL execution plans
- Technologies used: Java 21, Kotlin, Spring Boot 3, Angular, TypeScript, REST API, JSON, Kubernetes, Docker, PostgreSQL, Liquibase, Keycloak, OAuth2, GitHub Actions, Testcontainers, Azure Application Insights, Thymeleaf, Tilt, Microsoft SQL Server
Yannick Reinke
Last position:
Power Platform Developer at PWC
- Digitization and automation of internal business processes with the Microsoft Power Platform: analysis, design, and development of end-to-end solutions to increase company-wide efficiency
- Creating user-friendly interfaces with Power Apps
- Automating workflows and approval processes with Power Automate
- Visualizing process KPIs with Power BI
Elnazossadat Hosseininia
Last position:
Data Analyst at Siemens Healthineers
- Developed KPI dashboards using Power BI and DAX for 4+ business units, improving reporting transparency and strategic decision support.
- Migrated enterprise finance data views into dbt models, implementing modular SQL transformations, version-controlled data pipelines, and automated documentation to create a scalable analytics layer.
- Built dimensional data models in Snowflake for enterprise finance data, enabling scalable forecasting and supporting executive decision-making.
- Designed end-to-end ETL/ELT pipelines using Snowflake and SAP HANA, integrating data from 3+ enterprise systems.
- Automated monthly reporting workflows using SQL and Power BI, delivering strong business impact by reducing manual effort by 80%.
- Collaborated with finance stakeholders to translate business requirements into analytical data models, supporting strategic decision-making cycles.
- Delivered ad-hoc financial reports using Power BI, reducing turnaround time by 60%.
- Implemented data validation logic in SQL, resolving 95% of recurring data quality issues.
Discover over 15,000 top freelancers
Statistics of experts using Azure SQL Database
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
1.9 years
Positions per freelancer
13
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Manufacturing
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
97%
Master's degree or higher
70%
Doctorate
10%
Certifications per freelancer
3
Most common languages
English, German, French
Speak two or more languages
97%
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 Germany 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 Germany using Azure SQL Database
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
Core use
Azure SQL Database is Microsoft’s managed relational database service for cloud apps that need SQL Server compatibility without operating the database engine themselves. Teams use it for business systems, customer portals, reporting stores, and SaaS products that need predictable administration and clear scaling options.
Typical work
- Designing databases and schemas for new applications
- Migrating workloads from SQL Server or SQL Azure
- Tuning queries, indexes, and resource use
- Setting up backups, failover, and disaster recovery
- Supporting integration with Power BI, Azure App Service, and Logic Apps
Ecosystem fit
Azure SQL Database sits in the Microsoft Azure data stack and works well with SQL Server tools, Azure Portal, Azure CLI, ARM templates, and DevOps pipelines. Specialists often combine it with Azure Active Directory, Key Vault, and monitoring tools to keep access, secrets, and operations aligned.
When specialists matter
Companies bring in freelance experts when a migration must be clean, a production database is slow, or a service needs better partitioning, indexing, or security controls. In Germany, that often comes up in finance, logistics, industry, and software teams that want cloud delivery but still need close coordination in English or German.
What strong experts do
Strong professionals go beyond basic administration. They understand query plans, locking, networking, and service tiers, and they can explain trade-offs between single databases, elastic pools, and managed instance alternatives when the architecture changes.
Search terms and adjacent skills
Azure SQL Database is also commonly searched as Azure SQL, SQL Database, or the older name SQL Azure. Useful adjacent skills include T-SQL, Microsoft SQL Server, data migration, identity and access control, and observability. Good specialists connect all of these to the real workload, not just the product name.
Frequently asked questions
Not sure where to start with Azure SQL Database? These answers cover the essentials.
Azure SQL Database is used for cloud-hosted relational data in applications that need SQL Server-style querying without self-managing the full database server. Companies use it for customer systems, internal business apps, analytics staging, and SaaS back ends. It is a good fit when reliability, backup handling, and security controls matter.
Azure SQL Database removes much of the operating work that comes with SQL Server on a virtual machine, such as patching and many infrastructure tasks. A VM can still make sense when you need deeper OS-level control or special server features. For most app-focused workloads, the managed service is easier to run and maintain.
Azure SQL Database is usually the better choice when the application can work with a database-centric model and you want simpler scaling options. Azure SQL Managed Instance is closer to a full SQL Server instance and is often chosen for lift-and-shift migrations with more instance-level requirements. A good specialist helps decide based on compatibility, not habit.
A strong Azure SQL Database expert should know T-SQL, indexing, performance tuning, and migration planning. They should also understand Microsoft Azure basics such as identity, networking, monitoring, and secrets handling. The best professionals can work across application teams and explain database trade-offs clearly.
For Azure SQL Database, a good brief includes the current platform, data volume patterns, pain points, security needs, and whether the work is greenfield, migration, or rescue work. You do not need every detail solved upfront, but the expert should know what success looks like. That helps avoid wrong sizing and rework.
Yes, Azure SQL Database projects often work well with remote collaboration because most tasks are documented, reviewable, and tooling-driven. In Germany, some teams prefer a mix of remote work and onsite sessions for stakeholder alignment, especially during migration cutovers. A freelance specialist should be comfortable with both formats.
Look for clear examples of migrations, query tuning, backup and restore planning, and security setup on Azure SQL Database. Strong candidates explain why they chose a design, not just what they configured. They also ask about workload shape, recovery goals, and how the application uses the data.
Azure SQL Database is the current name; SQL Azure is the older name that many people still use in searches and conversation. The product evolved, but the core idea stayed the same: a managed Microsoft cloud database service built for relational workloads. When hiring, search both names to avoid missing the right specialist.
The average hourly rate of freelancers in Germany who have used Azure SQL Database in their recent projects is 92 €, which corresponds to a daily rate of about 738 € based on an 8-hour working day.
Of the freelancers in Germany who have used Azure SQL Database in their recent projects, 97% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Germany who have used Azure SQL Database in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Germany who have used Azure SQL Database in their recent projects are English (100%), German (97%), and French (19%).
The most common industries among freelancers in Germany who have used Azure SQL Database in their recent projects are Information Technology (89%), Banking and Finance (62%), and Manufacturing (43%).
The most common business areas among freelancers in Germany who have used Azure SQL Database in their recent projects are Information Technology (97%), Product Development (89%), and Business Intelligence (76%).
Main locations of FRATCH Experts, who have recently used Azure SQL Database
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.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
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FRATCH CEO
