Azure Data Factory Experts in Cologne
matched in minutes by AIHire experts who design cloud data pipelines, connect enterprise sources and orchestrate analytics workloads across Microsoft Azure. FRATCH helps you find precise matches with vetted, available freelancers for remote or on-site collaboration.
Meet FRATCH Experts in Cologne, who have recently used Azure Data Factory
Ravindra K.
Last position:
Data Engineer (Team Lead) at OPTUM – UnitedHealth Group
- Lakehouse build: Designed and built the member & eligibility domain of an Azure Databricks healthcare lakehouse, ingesting SQL Server, file and REST/SFTP sources (JSON, CSV, XML, Parquet) via Azure Data Factory into ADLS Gen2.
- Medallion pipelines: Transformed data through bronze, silver and gold Delta Lake layers with PySpark and Spark SQL; used Delta Live Tables / Lakeflow with built-in expectations for declarative, quality-checked pipelines.
- Platform modernisation: Delivered a SQL Server-to-cloud platform: ADF → ADLS Gen2 → Databricks → dbt Core models → Snowflake → Power BI, replacing legacy reporting with governed analytics.
- Robust ETL: Built metadata-driven, idempotent full, incremental and watermark-driven loads with schema evolution and failure-state handling, improving reliability and re-runnability.
- Data modelling: Designed Kimball star schemas with SCD Type 1 & 2 dimensions; tuned slow queries and pipelines using execution plans.
- Governance & security: Applied Unity Catalog RBAC, lineage and audit logging, with Azure Key Vault secrets and managed identities, to meet HIPAA and GDPR requirements.
- Leadership & mentoring: Led a 6-person team (2 data engineers, 2 analysts, BI developer, QA); mentored engineers, set delivery standards and coordinated with international stakeholders.
- Delivery & AI-assisted work: Ran CI/CD and work tracking in Azure DevOps; built Power BI semantic models with DAX and RLS; used Genie Code, Claude and Copilot to accelerate PySpark/SQL development, DAX and documentation.
Alexander B.
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
Rodion O.
Last position:
Founder, CTO & Managing Director at MYNR Product Mining GmbH
- Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
- Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
- Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
- Developed graph-based representations of product structures and dependencies for analytical reasoning.
- Designed and implemented an agentic AI framework for AI-supported decision workflows.
- Built scalable analytical microservices and integrated reporting through modern BI technologies.
- Coordinated backend, AI, and frontend development across the MYNR platform stack.
Jens H.
Last position:
#52 Test Manager in Safety-Critical Infrastructure at Telecommunications Company
- Network elements, network, operational and operator-related systems
- Supporting around 20 different products (managed agile)
- Requirements analysis and management (functional and non-functional)
- Test concept and planning (scope, test phases, effort, schedule, resources, organization, etc.)
- Aligning approach with clients and service providers
- Managing and assisting in creation of test cases for system, integration and end-to-end tests
- Guiding and supporting test execution
- Defect management and planning bug fixes with external providers
- Preparing and facilitating workshops
- Regular reporting and creating automated test reports
- Further development of agile testing methodology and configuration of supporting tools
- Conceptual support in developing a quality seal for rating product and service quality of internal and external providers
- Requirements engineering based on ISO/IEC 25010, Scrum, SaFE
- BMC Remedy, Atlassian Confluence, Atlassian Jira (including plugins Xray, Structure), Microsoft Office (incl. Visio), Obsidian, doxis document management system, Gitlab, Obsidian
Florian R.
Last position:
Senior Fullstack Developer at Ivii GmbH
- Two-month modernization of the management UI for AI-powered cameras
- Rewrote a complex React application to Vue 3 with single file components
- Set up the core architecture of the Vue application and configured Vite, Pinia, Router, I18n, ESLint, and Prettier
- Custom integration of Leaflet to display detection zones on images
- Assisted with backend extension and authentication adjustments
Giovanni S.
Last position:
Technical Product Manager at Logicc GmbH
Acted as the primary bridge between Legal, Engineering, and Business units to ensure zero compliance violations while maintaining product velocity.
Led the development of a GDPR-compliant AI aggregator platform, managing a roadmap that balances legal constraints with aggressive feature delivery.
Scaled the engineering team from 4 to 9 developers, establishing hiring protocols and technical onboarding processes to support rapid product iteration.
Boosted the development process by introducing structured sprint cycles and backlog refinement, resulting in a 20% reduction in feature delivery time.
Architected and prototyped agentic AI workflows with n8n and RAG pipelines on Langchain.
Discover over 15,000 top freelancers
Statistics of experts using Azure Data Factory
Aggregated from the professional profiles of matched freelancers.
Experience
20 years (Germany: 16 years)
Position duration
2.7 years (Germany: 2.1 years)
Positions per freelancer
13 (Germany: 11)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Human Resources
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
80% (Germany: 63%)
Certifications per freelancer
4
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 5 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Cologne are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Cologne using Azure Data Factory
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 5 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Azure Data Factory 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 (100%)
- Banking and Finance (67%)
- Professional Services (67%)
- Healthcare (50%)
- Aerospace and Defense (33%)
- Automotive (33%)
- Education (33%)
- Food and Beverage (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Azure Data Factory does
Azure Data Factory is Microsoft Azure’s managed service for moving, transforming and orchestrating data. It connects databases, files, SaaS applications, APIs and cloud storage, then runs repeatable pipelines for reporting, analytics and machine learning. Teams use it to replace manual transfers with controlled, observable workflows.
Pipelines and integration
A pipeline in Azure Data Factory combines activities, datasets, linked services and triggers. Specialists configure copy jobs, mapping data flows, parameters, variables, dependency rules and failure handling. They can integrate Azure Data Lake Storage, Azure SQL, Synapse Analytics, Databricks, Snowflake and on-premises systems through self-hosted integration runtimes.
Typical delivery work
- Design batch and incremental ingestion pipelines
- Connect on-premises sources with Azure services
- Transform structured and semi-structured data with mapping data flows
- Schedule, monitor and retry production workloads
- Deploy pipelines across development, test and production environments
The work often includes metadata-driven processing, schema management, data quality checks and secure movement of sensitive information. Good specialists document dependencies so other teams can operate and extend the solution.
When companies need expertise
Companies usually bring in freelance expertise when a migration to Azure has started, existing pipelines are unreliable or a reporting landscape needs a dependable data foundation. They may also need help replacing SSIS packages, connecting fragmented systems or preparing data for Synapse and Power BI. In Cologne, professionals may support local teams on-site while coordinating with distributed stakeholders remotely.
Skills around the service
Strong Azure Data Factory professionals understand more than the visual pipeline designer. Useful adjacent skills include SQL, Python, Azure identity and networking, Git, CI/CD, infrastructure as code, dimensional modelling and monitoring with Azure Monitor or Log Analytics. Familiarity with Azure Data Lake Storage, Azure Synapse Analytics, Databricks and Microsoft Purview helps when the service is part of a wider data platform.
Choosing a strong specialist
Look for someone who can explain source systems, data volumes, security boundaries, recovery paths and operational ownership in concrete terms. Review examples of incremental loading, late-arriving data, schema changes and deployment automation rather than only screenshots of pipelines. A capable professional balances delivery speed with cost control, clear documentation, access governance and measurable data quality.
Frequently asked questions
Key details about Azure Data Factory, drawn from the questions we get asked most.
Azure Data Factory is used to ingest, transform and schedule data across cloud and on-premises systems. Companies use it for reporting pipelines, data lake loading, warehouse preparation, application integration and recurring analytics workflows.
Azure Data Factory is a managed cloud service designed for orchestration and broad connectivity, while SSIS is a package-based integration technology often hosted through SQL Server or Azure-SSIS Integration Runtime. A specialist can assess whether to migrate existing packages, rebuild them as native pipelines or use both approaches together.
Azure Data Factory and Synapse pipelines use closely related orchestration concepts and interfaces. Synapse adds those capabilities inside an analytics workspace, while Azure Data Factory is a dedicated integration service; the right choice depends on governance, workload boundaries and the surrounding Azure architecture.
A strong Azure Data Factory specialist usually works comfortably with SQL, Azure Data Lake Storage, Azure identity, Git and deployment automation. Experience with Synapse Analytics, Databricks, Power BI, Python, monitoring and data modelling is valuable for end-to-end delivery.
The right Azure Data Factory experience depends on the scope, source complexity and operational risk. A straightforward ingestion flow may need focused pipeline expertise, while a migration or regulated data platform calls for a professional who has handled security, incremental loads, release processes and production incidents.
Azure Data Factory projects are often suitable for remote collaboration because pipelines, source mappings and deployments are managed digitally. On-site sessions in Cologne can still help with access reviews, legacy-system discovery and workshops with business or infrastructure teams.
Ask an Azure Data Factory professional to explain retry logic, dependency handling, monitoring, secrets management and deployment between environments. Strong answers should address schema changes, failed loads, data validation, documentation and who operates the pipelines after delivery.
Working with Azure Data Factory requires careful attention to integration runtimes, permissions, network access, trigger behaviour and service limits. Specialists should also be comfortable clarifying source ownership, documenting assumptions and coordinating with security, analytics and infrastructure teams.
The average hourly rate of freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects is 84 €, which corresponds to a daily rate of about 673 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects, 100% hold at least a Bachelor's degree and 80% hold at least a Master's degree.
On average, freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects are German (100%), English (100%), and Spanish (33%).
The most common industries among freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects are Information Technology (100%), Banking and Finance (67%), and Professional Services (67%).
The most common business areas among freelancers in Cologne, Germany who have used Azure Data Factory in their recent projects are Information Technology (100%), Product Development (100%), and Business Intelligence (83%).
Main locations of FRATCH Experts, who have recently used Azure Data Factory
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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