Change Data Capture Experts in Germany
, matched fast from over 15,000 CVsHire experts who design log-based data pipelines, configure Debezium and Kafka Connect, and connect operational databases with warehouses or event-driven services. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Change Data Capture
Kiriakos K.
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
Maturing their API practices on both a business and technology level. My role covers strategy, architecture, developer advocacy as well as hands-on software engineering, enabling both technical teams and business leadership to adopt and act on API-centric principles effectively. Coincidentally, we also establish GitOps, DX and platform best practices with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, React, Node.js, TypeScript, Redocly, reactive programming, CDC, Golang, Gin, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Ali A.
Last position:
Founder & Architect at Independent AI R&D
- Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
- GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
- AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Frank E.
Last position:
DevOps at Lauck-IT
Operations and extensions of Azure DevOps pipelines
Operations and extensions of AWS services
Citrix (Windows 10, Bitwarden)
AWS: ECR, EKS, CloudFront CDN, Route 53, VPC peering and CNI upgrade, Atlas MongoDB, S3 buckets, static website hosting
Azure: build and deploy with DevOps pipelines
Hardeep B.
Last position:
Sr. Data Engineer at Charles Schwab Bank
- Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
- Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
- Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
- Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
- Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
- Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
- Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
- Created and maintained dashboards in Power BI to provide actionable insights.
Umut G.
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.
Klaus E.
Last position:
Exasolution DBA at Rechenzentrum Innsbruck
- DBA Exasolution Server consulting and migration to version 8
- Analysis of SQL query performance and tuning
- Troubleshooting in batch scripts
- Technologies: Gitlab, EXACloud, EXAOperation, DBeaver, Control M
Felix R.
Last position:
SAP Analytics & Planning Expert at RWS GmbH
- Greenfield implementation of S/4HANA Embedded Analytics as well as reporting and planning processes with SAP Analytics Cloud (SAC).
- Integrated production, sales, and inventory planning, as well as financial planning and management reporting.
- Inventory forecasts implemented through SAC Machine Learning.
- Integration of S/4HANA data and HR data (Factorial) into SAP Datasphere (various tables with real-time replication, related data flows, and analytical models)
Benjamin S.
Last position:
Design and implementation of a new cloud service at Porsche AG
- Design of a new cloud service
- Requirements Engineering
- API Design (REST API, Kafka)
- Consulting on architecture, feasibility and effort estimation
- Implementation of a microservice architecture
- Implementation of a Spring Boot web service
- Development of REST APIs including business and persistence logic
- Kafka consumers and producers
- Various Excel upload/download scenarios
- Change Data Capture
- Cloud provisioning with IaC/Terraform
- Go-live with 30,000 users
- Operation, support and bug fixing for other services
Environment/tools: GitLab, JIRA, Confluence, IntelliJ, Spring Boot, Java, Docker, Terraform, AWS ECS, Postgres, Apache Kafka, SAP Datasphere, JUnit, Debezium, Apache POI, Hibernate, JPA, Testcontainers
Peter B.
Last position:
Data Warehouse Consultant (Development and Analysis) at Atruvia AG
- Developed and enhanced ETL loading jobs with IBM DataStage and optimized SQL in an IBM DB2 environment as part of the Agree21 data migration
- Analyzed data quality and developed test procedures
- Created PowerShell scripts and documented GIT deployment processes
- Technologies: RedHat Linux, IBM DB2 with DBVisualizer, IBM InfoSphere DataStage 11.7, JIRA, TortoiseGIT, TortoiseSVN, PowerShell scripts
Asad K.
Last position:
Senior AI Developer at Neuland.ai AG
- Architected and deployed a production-scale GraphRAG system using Neo4j, embeddings, and multi-hop reasoning over 120M+ nodes, improving answer precision by 32%, reducing hallucinations by 41%, and lowering retrieval latency by 38%.
- Designed and implemented an enterprise agent ecosystem using Model Context Protocol (MCP), exposing internal APIs, databases, and services as secure callable tools for autonomous workflows and system integration.
- Designed and deployed a production LLM-based email routing agent using Microsoft Graph API, MCP, and Azure OpenAI, achieving 96% routing accuracy, reducing manual triage workload by 65%, and decreasing response times from 18 hours to under 4 hours.
- Implemented autonomous agent self-correction pipelines using iterative feedback loops (Ralph Wiggum), enabling reliable error detection, automated remediation, and production-safe execution.
- Developed a multimodal semantic search platform using multimodal LLMs and vector embeddings, enabling semantic discovery across 250k+ image and video assets and improving search recall by 48%.
Vladislav L.
Last position:
Freelance Data Engineer / Architect at Deutsche Bank
Designed and implemented a scalable data lake on Google Cloud Platform (GCP) for the Anti-Financial Crime (AFC) division, supporting Anti-Money-Laundering and Counter-Terrorism-Financing initiatives
Built robust data pipelines for ingesting and processing over 30 million daily transactions from retail and corporate banking, applying dimensional modeling to enable advanced analytics and regulatory reporting
Ensured resilience by implementing change data capture, late-data handling, and schema evolution across evolving source systems
Led a small engineering team and collaborated with international stakeholders in Germany, Singapore, Sri Lanka, Hong Kong, Taiwan, and Thailand to ensure compliance, data quality, and performance
Google Cloud Platform (GCP)
Apache Spark (Dataproc & Cloudera Data Platform - Python PySpark)
Apache Airflow (Cloud Composer - Python API)
Google Cloud Storage
BigQuery
GitHub Actions
Terraform
Google Kubernetes Engine (GKE)
Discover over 15,000 top freelancers
Statistics of experts using Change Data Capture
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
1.8 years
Positions per freelancer
12
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
92%
Master's degree or higher
42%
Certifications per freelancer
5
Most common languages
English, German, French
Speak two or more languages
92%
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 Change Data Capture
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.
Change Data Capture 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 (58%)
- Automotive (50%)
- Telecommunication (42%)
- Manufacturing (33%)
- Media and Entertainment (33%)
- Pharmaceutical (33%)
- Professional Services (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What CDC does
Change Data Capture, often called CDC, records inserts, updates and deletes as they happen in a source system. Instead of repeatedly copying complete tables, it sends only changed records to downstream systems. This supports fresher data while reducing load on operational databases.
Where it runs
CDC is used to build data platforms, event-driven services and operational reporting flows. Common destinations include cloud warehouses, lakehouses, search indexes, caches and customer-facing applications. Retail, finance, logistics and manufacturing teams use it wherever several systems must stay aligned.
- Replicate database changes to analytics platforms
- Feed events into streaming and messaging systems
- Keep services and read models synchronized
- Support migrations with controlled data movement
Ecosystem and tooling
Strong CDC work connects database internals with streaming infrastructure. Specialists may work with PostgreSQL logical replication, MySQL binlogs, SQL Server change tracking, Oracle redo logs, Debezium, Kafka Connect, Apache Kafka, cloud-native change streams and managed services such as AWS DMS. Schema registries, data contracts, connectors and observability complete the setup.
When expertise matters
Freelance expertise helps when an existing integration is too slow, creates duplicate events or cannot explain data gaps. It is also valuable during database migrations, warehouse modernisation, merger integration and the rollout of event-driven architecture. In Germany, remote collaboration is common, while regulated or industrial environments may require on-site workshops and clear documentation in English or German.
- Source databases are under pressure from repeated exports
- Reports need fresher data than batch jobs provide
- Teams need reliable replay, recovery and ordering
- A migration must run without extended downtime
Delivery and safeguards
A sound implementation defines the change event, key, ordering rules and delivery guarantees before a connector is deployed. Professionals handle snapshots, offsets, schema evolution, deletes, retries, backfills and access controls. They also monitor lag, failures and data quality across the full path rather than treating the connector as a standalone tool.
What good looks like
The right specialist can explain trade-offs between log-based CDC, triggers, timestamp polling and native change streams. They test failure recovery, validate source-to-target reconciliation and document operational ownership. Look for experience with the relevant database engines, streaming patterns, security requirements and the business meaning of the data, not only familiarity with a named product.
Frequently asked questions
What clients ask us most about Change Data Capture — answered in short.
Change Data Capture captures database changes and delivers them to other systems without repeatedly reading complete tables. Companies use CDC for warehouse loading, application synchronization, event processing, migrations and near-real-time reporting.
CDC usually has less source-system overhead and lower data delay because it follows committed changes rather than repeatedly scanning records. Polling can be simpler for small integrations, while batch replication may be more suitable when freshness is not important.
A strong Change Data Capture specialist may work with Debezium, Kafka Connect, Apache Kafka, PostgreSQL logical replication, MySQL binlogs and cloud migration services. Useful adjacent skills include data modelling, schema evolution, event design, SQL, observability, security and cloud infrastructure.
A small, well-understood source can often be handled by a specialist who has delivered comparable connectors and recovery procedures. Complex estates need deeper experience with transaction ordering, snapshots, deletes, schema changes, replay, compliance and cross-system reconciliation.
Change Data Capture work is often suitable for remote collaboration because configuration, testing and monitoring can be handled through shared environments. On-site sessions may still help with network access, regulated data, factory systems or workshops involving several German-speaking teams.
CDC can produce incorrect results when teams overlook deletes, duplicate delivery, transaction boundaries or schema changes. Other risks include unbounded lag, incomplete snapshots, weak access controls and a lack of reconciliation between source and destination.
Ask a Change Data Capture specialist to explain recovery after connector failure, handling of out-of-order events and validation of source-to-target completeness. Good professionals discuss operational runbooks, measurable data-quality checks and the limits of their chosen tool instead of promising that a connector will solve everything.
A CDC assignment is rarely just connector configuration. Freelancers should clarify source database behaviour, target guarantees, security boundaries, ownership of incidents, expected freshness, schema governance and whether the team can support the pipeline after delivery.
The average hourly rate of freelancers in Germany who have used Change Data Capture in their recent projects is 95 €, which corresponds to a daily rate of about 757 € based on an 8-hour working day.
Of the freelancers in Germany who have used Change Data Capture in their recent projects, 92% hold at least a Bachelor's degree and 42% hold at least a Master's degree.
On average, freelancers in Germany who have used Change Data Capture in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Germany who have used Change Data Capture in their recent projects are English (100%), German (92%), and French (17%).
The most common industries among freelancers in Germany who have used Change Data Capture in their recent projects are Information Technology (100%), Banking and Finance (58%), and Automotive (50%).
The most common business areas among freelancers in Germany who have used Change Data Capture in their recent projects are Information Technology (100%), Business Intelligence (83%), and Project Management (75%).
Main locations of FRATCH Experts, who have recently used Change Data Capture
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
