DataOps Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used DataOps
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
Vili D.
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, 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 EMEA at Aparavi Software Europe GmbH
- Always looking for solutions to problems and finding ways to tackle business challenges
- Leading and managing large multi-disciplinary teams (product development, project management, engineering, operations, QA, solution management, customer success)
- Developing and executing innovation and digitalization strategies for complex transformation projects
- Acting as Information Security Officer, planning, conducting, and successfully completing all ISO 27001:2022 standard audits and continuously ensuring compliance
- Leading and coaching managers across the organization
- Representing the company at industry events and coordinating external partnerships
- Providing technical support to the Aparavi sales team
- Working with account managers to lead and grow enterprise customers
- Collaborating with technical and non-technical customer departments to manage and meet expectations (e.g., C-level, finance, IT services, data security and works council)
- Leading technical integration and coordinating seamless solution implementation
- Hands-on development and management of cloud, AI, and SaaS solutions to meet demanding customer expectations
- Promoting agile, DevOps-based methods and organizational structures for innovation and sustainable growth
- Continuously analyzing and solving technical and business challenges to boost company success
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.
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-driven processes, methods, systems, and applications (Data-Driven Company) in data management and agile requirements engineering.
Identifying essential use cases and (non-functional) requirements to build an architecture on the one hand.
Optimizing clients' internal processes and developing training plans for new technologies and methods.
Combining technical know-how (for example, data analysis in cloud data analytics environments through semantic layers) with key soft skills such as agility, teamwork, creativity, and analytical competence.
Emphasis in data management on efficient use of systems as well as the simple application of technologies for data engineering, data cataloging, virtualization, exploration, and visualization.
Operationalizing both infrastructure as well as data and mathematical analytical models (DevOps, DataOps, MLOps).
Acting as a link between architecture, business departments, development, and operations, taking into account essential core areas such as data governance, data security, and data quality.
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
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
Business Intelligence, Information Technology, 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 19 Sep 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 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 19 Sep 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%)
- Transportation (33%)
- Aerospace and Defense (22%)
- Insurance (22%)
- Retail (22%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
DataOps in practice
DataOps, also called Data Operations, applies software delivery and operations principles to data work. It connects ingestion, transformation, testing, orchestration and monitoring so teams can deliver trusted data to analytics, reporting and machine learning systems.
What it delivers
DataOps professionals build and maintain reliable data products across the full lifecycle. Typical work includes:
- Automated batch and streaming pipelines
- Tested data transformations and reusable models
- Data quality checks, lineage and observability
- Governed datasets for analytics and machine learning
Tools and ecosystem
The ecosystem spans cloud warehouses, lakehouses, integration tools and orchestration frameworks. Specialists may work with dbt, Apache Airflow, Dagster, Kafka, Snowflake, Databricks, BigQuery or Azure and AWS data services. Python, SQL, Git, containers and CI/CD support repeatable delivery.
When expertise matters
Companies bring in freelance DataOps expertise when pipelines become fragile, ownership is unclear or new platforms must be adopted without disrupting reporting. In Germany, specialists often support distributed teams across regulated industries, manufacturing, finance and logistics, combining remote delivery with on-site workshops when needed.
Signs you need support
A focused specialist can help when data work shows recurring operational gaps:
- Pipeline failures are discovered by business users
- Definitions differ between reports and teams
- Manual releases slow down data delivery
- Cloud migration leaves orchestration and testing unresolved
Strong professional practice
Strong DataOps professionals design for reliability rather than simply moving data from one system to another. They define ownership, test business rules, document lineage and measure freshness and completeness. They also explain trade-offs clearly, protect sensitive data and leave maintainable workflows that internal teams can operate.
Frequently asked questions
Questions about DataOps? Start with the answers below.
DataOps is used to make data delivery more reliable, repeatable and observable. It supports ingestion, transformation, validation and publication for analytics, reporting, operational decisions and machine learning.
DataOps adds stronger operational practices to data work, including automated testing, deployment controls, monitoring and shared ownership. It complements data engineering by focusing on the continuous delivery and quality of usable data products.
A capable DataOps freelancer may work with dbt, Apache Airflow, Dagster, Kafka, Snowflake or Databricks, depending on the environment. SQL and Python are common foundations, alongside Git, CI/CD, cloud services and data observability tools.
Strong DataOps work often requires cloud architecture, data modeling, platform security and business intelligence knowledge. Experience with governance, lineage, infrastructure as code and machine learning pipelines can also be valuable.
The right DataOps experience depends on the scope and risk of the work. A pipeline improvement may need focused delivery skills, while a platform redesign calls for someone who can set standards, handle migrations and align several teams.
DataOps is well suited to remote collaboration when repositories, environments and documentation are accessible to the whole team. For German companies, clear communication in English may be sufficient for some projects, while German can matter for stakeholder workshops and regulated business processes.
A DataOps approach becomes useful when data has multiple consumers, frequent changes or strict quality expectations. A simple schedule may be enough for a small, stable flow, but it offers less control over testing, lineage, recovery and release management.
Ask how the DataOps professional handles failed runs, schema changes, data quality rules, observability and rollback. Strong answers connect technical controls to business definitions and show how internal teams will operate and improve the resulting workflows.
The average hourly rate of freelancers in Germany who have used DataOps in their recent projects is 118 €, which corresponds to a daily rate of about 944 € 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 Business Intelligence (100%), Information Technology (100%), 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
