DataOps Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used DataOps
Vili D.
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility
Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture
Pipeline orchestration with Azure Data Factory
Improved and automated the development and deployment process by integrating Git and GitHub Actions
Technical leadership of the Data Engineering team (3 employees)
Led workshops to optimize and stabilize the data platform and development process
Collected and prioritized new requests and maintained the product backlog
Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural
Zakaria A.
Last position:
Vice President Technology at APARAVI Software GmbH
- Lead Presales, R&D, Product, and Engineering for EMEA region – remote/hybrid, multicultural teams of 30+
- Serve as Information Security Officer (ISO), leading ISO 27001 certification efforts and conducting regular security audits
- Implement and maintain comprehensive information security management systems (ISMS) ensuring compliance with GDPR, DORA, and international regulations
- Architect data intelligence, SaaS, and unstructured data solutions using AI, ML, and cloud-native tech
- Drive solution sales initiatives, conduct technical demonstrations and engage with enterprise customers to deliver tailored solutions
- Engaged in hands-on pilots with cutting-edge cloud platforms, Generative AI, and edge computing
- Represent company in major industry forums – regular interface with C-level, customers, and partners
- Delivered proven 35-45% cost/complexity reduction with innovative, automated compliance and privacy frameworks.
Tezcan D.
Last position:
Solution Architect / Project Manager at German Football Association
- Overall responsibility for the project lifecycle from scope definition to completion
- Close collaboration with platform teams, IT leaders, and external service providers
- Application of SAFe principles and structured sprint work
- Creation of a migration roadmap with clear milestones
- Monitoring of the lifecycle: onboarding, repository migration, replication of permissions, and system tests
- Visualization of the architecture with PlantUML and Gliffy as well as documentation in Confluence
- Regular status reports and running knowledge transfer sessions
Louis G.
Last position:
Freelance Solutions Architect and Machine Learning Engineer at Self-employed
- Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
- Work with customers to understand their challenges and provide the best solutions based on open-source data products
- Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
- Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
- Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
- Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
- Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
- Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible
Moritz K.
Last position:
Senior DevOps Engineer GCP at tedi GmbH & Co. KG
- Design and implementation of DevOps and CI/CD practices for data and analytics teams
- Introduction of infrastructure as code with Terraform (IaC)
- Setup and maintenance of GCP user and permission management with Terraform in multi-project environment
- Design and implementation of CI/CD pipelines with GitHub
- Leading and training developer team for the introduction of IaC and CI/CD practices
- Building and optimising database connectors with Apache Arrow for terabyte scale data extraction (Oracle, SAP)
- Optimising data lake storage and warehouse ingest
Torsten G.
Last position:
Data Vault with Informatica on Oracle at SEFE
- Data Vault modeling and performance improvements in Oracle.
- Requirements process with model-driven Data Vault automation.
- Preparation of business requirements for the price database in the gas and electricity market.
- Sales performance based on Salesforce CRM.
- Tasks: Concept and development.
- Tools used: Informatica, Oracle, DBT, Docker, DataOps, Airflow Workflow, Python Ingestion, Gitlab CI.
Felix M.
Last position:
Business Developer, Product Owner Support at VisualVest, digital asset manager (robo-advisor) of Union Investment
- Development of an innovative platform for topics and questions around next-generation investments as part of new business models
- Analysis of product ideas
- Coordination of new features with UX/UI (in Figma) and developers
- Creation of user stories in Jira: description/open topics/preconditions/requirements/error handling/audit log/UX/UI/technical hints/test scenario/acceptance criteria
- Conducting tests and documenting test results
- Creation and management of defects
- Coordination of sprint planning and backlog with product owner and Scrum Master
- Preparation of sprint review presentations
- Project implementation with Scaled Agile Framework (SAFe): stage planning in Conceptboard with Magic Estimations, feature/kanban board, sprint planning, functional refinement, sprint backlog, daily standups, sprint review, sprint retrospective
- Platform with the latest technological market standards: Angular (frontend framework), Jakarta EE, Matamo Tracking, Keycloak, movingimage
Markus G.
Last position:
Data Solution Architect, Founder at GRITCON GmbH
- Design and development of modern cloud DWH & data platforms
- Data Vault automation
- Implementation of ELT and CI/CD processes
- Requirements analysis and data modeling
- Building an automated cloud data platform as a reference architecture for financial risk controlling (Snowflake, Data Vault, DBT, Python, GitHub) 2024-10-01 – 2025-06-30, Zurich
- DWH further development, operations and cloud migration (Data Vault, DBT, SAP Data Services, Alteryx, SQL Server, Azure Synapse) 2023-03-01 – 2025-06-30, Frankfurt
- Implementation of a global cloud data platform (Data Vault, WhereScape, Snowflake, AWS, Scrum) 2021-04-01 – 2023-12-31, Cologne
- Proof of concept for a global cloud data platform (Data Vault, Snowflake, Synapse, WhereScape, Azure, Scrum) 2022-04-01 – 2022-07-31, Bonn
- Implementation of a cloud data platform (Data Vault, Snowflake, WhereScape, AWS) 2021-07-01 – 2022-04-30, Karlsruhe
- Big data integration of all source systems related to the ITSM process (Data Vault, Snowflake, WhereScape, AWS, Scrum) 2021-01-01 – 2021-05-31, Prague
- Development and operation of a global self-service BI platform to display around 150 corporate KPIs (Data Vault, WhereScape, Postgres, Jenkins, Talend, AWS, Scrum) 2018-11-01 – 2020-12-31, Frankfurt
- Implementation of a DWH for price management and capacity forecasting in long-distance passenger transport (SAP BODS, SQL Server, AWS) 2017-10-01 – 2018-11-30, Frankfurt
- Introduction of SAP BODS and migration of the existing DWH (SAP, BODS, HANA, Oracle, Cognos) 2017-05-01 – 2017-10-31, Rastatt
Oliver R.
Last position:
Trainer and Solution Architect for Data Management, Data Mesh, Data Fabric, Observability, Big Data Technologies, Advanced
Supporting national and international companies in building data-centric processes, methods, systems and applications (Data-Driven Company) in the areas of Data Management and agile Requirements Engineering.
Identifying essential use cases and (non-functional) requirements to build an architecture from them.
Optimizing the client's internal processes and developing training plans for new technologies and methods.
Combining technological know-how (for example, for data analysis in Cloud Data Analytics environments through semantic layers) with important soft skills such as agility, team skills, creativity and analytical competence.
Focusing in the area of Data Management on the efficient use of systems and the simple use of technologies for Data Engineering, data cataloging, virtualization, exploration and visualization.
Operationalizing infrastructure as well as data and mathematical and analytical models (DevOps, DataOps, MLOps).
Acting as the link between architecture, business departments, development and operations while taking essential core areas such as Data Governance, Data Security and Data Quality into account.
Discover over 15,000 top freelancers
Statistics of experts using DataOps
Aggregated from the professional profiles of matched freelancers.
Experience
21 years
Position duration
5.3 years
Positions per freelancer
17
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
86%
Master's degree or higher
71%
Doctorate
29%
Certifications per freelancer
5
Most common languages
German, English, French
Speak two or more languages
89%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany 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 Germany using DataOps
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
DataOps 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%)
- Automotive (67%)
- Banking and Finance (44%)
- Professional Services (44%)
- Aerospace and Defense (33%)
- Transportation (33%)
- Insurance (22%)
- Retail (22%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What DataOps covers
DataOps is an operating model for delivering reliable, timely and usable data. It combines data engineering, quality management, testing, orchestration, security and collaboration in one controlled workflow. The goal is repeatable data delivery that supports analytics, reporting, machine learning and operational decisions.
Where it is used
Companies use DataOps to connect source systems with warehouses, lakehouses and analytical products. Typical work includes:
- Automating ingestion from applications, databases and APIs
- Validating data before it reaches reports or models
- Managing batch and streaming pipelines
- Monitoring freshness, completeness and pipeline health
- Supporting governed self-service analytics
Tools and ecosystem
DataOps specialists work across an ecosystem rather than one fixed product. Common components include Apache Airflow, dbt, Apache Kafka, Spark, SQL, Python and Git-based delivery workflows. They may also use Snowflake, Databricks, BigQuery, Microsoft Fabric or cloud services from AWS, Azure and Google Cloud, depending on the existing architecture.
When companies need support
Freelance expertise is useful when pipelines are unreliable, ownership is unclear or data teams cannot release changes safely. It also helps during warehouse migrations, lakehouse projects, platform consolidation and the introduction of machine learning operations. In Germany, specialists often work with regulated industries that need clear lineage, access controls and dependable reporting while coordinating with local teams and remote stakeholders.
What strong specialists deliver
A strong professional maps data flows before changing them and makes dependencies visible. They define quality checks, incident procedures, deployment standards and useful operational signals rather than adding tools without a clear purpose. They can explain trade-offs to analysts, product teams, security specialists and business owners, and leave behind documentation that internal teams can maintain.
Remote and on-site collaboration
DataOps work can often be delivered remotely because pipelines, repositories and cloud environments are accessed digitally. On-site collaboration may be valuable during discovery, workshops or sensitive migration work. Companies should align early on German or English communication, access approval, documentation standards and responsibility for incidents, releases and data quality decisions.
Frequently asked questions
Questions about DataOps? Start with the answers below.
DataOps is used to make data collection, transformation, validation and delivery more reliable. It helps teams provide trusted datasets for business intelligence, reporting, machine learning and operational applications.
DataOps extends data engineering with stronger operational practices, including automated testing, monitoring, collaboration and controlled releases. Data engineering focuses on building pipelines and data systems, while DataOps also governs how those systems are changed and operated.
A strong DataOps specialist often combines SQL and Python with orchestration, cloud infrastructure, version control and data modelling. Useful adjacent skills include dbt, Apache Airflow, Kafka, observability, security, CI/CD and data governance.
The right level depends on the systems, risk and scope of the project. A smaller pipeline improvement may need focused expertise, while a platform migration or governance initiative benefits from a professional who has handled complex dependencies, incidents and stakeholder coordination.
DataOps is well suited to remote collaboration because repositories, cloud platforms and monitoring tools are accessible online. On-site sessions can still help with discovery, security reviews or workshops, especially when teams need to coordinate German and English communication.
Companies often bring in a DataOps freelancer when pipelines fail regularly, data quality is difficult to measure or releases depend on manual work. Freelance support is also useful for migrations, new warehouse implementations and setting up practical operating standards.
Look for clear pipeline ownership, measurable quality checks, useful monitoring and documented recovery procedures. Good DataOps work makes failures easier to detect, explains data lineage and enables safe changes without creating unnecessary operational complexity.
Data Operations is the expanded term commonly shortened to DataOps. Both describe practices for coordinating data development and operations, with emphasis on automation, testing, observability, governance and dependable delivery.
The average hourly rate of freelancers in Germany who have used DataOps in their recent projects is 119 €, which corresponds to a daily rate of about 950 € based on an 8-hour working day.
Of the freelancers in Germany who have used DataOps in their recent projects, 86% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 29% hold a doctorate.
On average, freelancers in Germany who have used DataOps in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 5.3 years.
The most common languages among freelancers in Germany who have used DataOps in their recent projects are German (100%), English (89%), and French (33%).
The most common industries among freelancers in Germany who have used DataOps in their recent projects are Information Technology (100%), Automotive (67%), and Banking and Finance (44%).
The most common business areas among freelancers in Germany who have used DataOps in their recent projects are Information Technology (100%), Business Intelligence (89%), and Product Development (78%).
Main locations of FRATCH Experts, who have recently used DataOps
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
