Data Pipeline Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used Data Pipeline
Justina Kmiecik
Last position:
Freelance Consultant for Change & Data Transformation at Freelance Fast Data Consulting
Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present
- Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
- Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.
Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025
- Concept development and solution design for new end-to-end processes including technical interfaces
- Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
- Analysis and validation of data models
- Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
- Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
- Documentation and comments on technical and business requirements to support implementation in agile squads
Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present
- Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
- Development of business solution concepts for migration to the target system, including system integration and data flows
- Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
- Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
- Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.
Monika Thepale
Last position:
Senior ETL Lead at Takeda GmbH
- Led design, development, and deployment of data solutions supporting a major pharma acquisition for Takeda Pharmaceutical Company, delivering transparency reporting systems across Azure,Databricks (Python and Shell Scripting) platforms.
- Owned,Designed and developed scalable ELT pipelines to process Customer and Product data using Azure, complex SQL, Databricks, and shell scripting, enabling efficient data integration and processing across multiple sources including job orchestration and workflow automation.
- Implemented performance optimization techniques (query tuning, parallelism, workload optimization), improving system efficiency and processing time.
- Applied strong analytical and problem-solving skills to assess technical solutions and support business requirements for compliance and transparency reporting.
- Designed scalable data foundations suitable for downstream analytics and AI workloads.
- Led data quality initiatives by assessing multiple source data, defining quality metrics, and establishing processes for monitoring and continuous improvement.
Tan Pham
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Basil Sattler
Last position:
Senior Developer / Data Engineer at Large energy-sector company
- Co-founded the Real-Time Data team, which grew to 10 members over time.
- Developed and delivered core data products.
- Optimized real-time application performance and implemented monitoring, alerting and logging solutions to ensure system stability.
- Created and maintained deployment pipelines.
- Collaborated with teammates, architects and experts in an agile Scrum environment.
- Operated applications, analyzed, tested and troubleshot software solutions.
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.
Ashkan Zadeh
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Kevin Meinon
Last position:
Backend & Infrastructure Engineer at Mileo Systems GmbH
- Engineered production-ready Azure environments using Terraform, ensuring consistent infrastructure parity across VNets and Resource Groups
- Implemented Microsoft Fabric tenant and workspace architecture for multi-stage Medallion data processing pipelines
- Designed secure data pathways using Managed Private Endpoints for isolated Azure Storage access
- Managed Service Principals and authentication tokens for secure REST API integrations
Marie-Josée Mache
Last position:
Java Engineer / Developer at Davaso GmbH
- Involved in the full development lifecycle, including design, coding, testing, and deployment of Java-based applications.
- Built and maintained high-performance RESTful APIs and microservices, ensuring scalability and reliable data exchange.
- Practiced code reviews, used version control systems (e.g., Git), and collaborated closely with cross-functional teams to deliver robust software solutions.
- Implemented, managed, and optimized complex business logic and decision-making processes using the Drools Rules Engine, leveraging DRL (Drools Rule Language) for dynamic configuration.
- Developed software solutions for a major service provider in the healthcare insurance sector, specifically focusing on claims processing and reconciliation logic to ensure cost-effective reimbursement for health funds.
Eduard Van Kleef
Last position:
Workshop Leader 'Introduction to AI Development Tools' at Software company in Wiesbaden
- Presentation introducing generic AI and large language models
- Explanation of legal frameworks (EU AI Act, US CLOUD Act, GDPR)
- Systematic review of AI tools along the SDLC and holistic systems
- Comparison of on-prem LLMs vs. cloud-based, as well as change management and works council
- Facilitated the discussion and derived next steps for introducing AI development tools
Jonas Walter
Last position:
Fullstack Developer at Soulven Agency
- Working for customer and internal projects ranging from B2C, B2B applications
- Development and maintenance of customer-facing and internal applications across B2C and B2B domains
- Responsibility for technical direction, architectural decisions and code quality standards
- Design and implementation of scalable application architectures, including modular frontend and service-oriented backend structures
- Conceptual planning and technical execution of the agency website relaunch in Angular
- Rapid prototyping and MVP development for B2B customer projects in the pharmaceutical sector with Vue.js
- Creation of first MVPs for 3D rendering–based products, including real-time visualization and interactive experiences
- Strong UX/UI expertise with a focus on gamification, user engagement and conversion-driven interfaces
- Close collaboration with product management, design and stakeholders to translate business requirements into technical solutions
- Agile software development using Scrum, including sprint planning, reviews and retrospectives, supported by Azure DevOps
- Full-stack development using React, Angular, TypeScript, Vue.js, HTML5, CSS3/SCSS, C#, .NET, Node.js, RESTful APIs, Unity, Azure DevOps, Git and CI/CD pipelines
Jana Chalak
Last position:
Freelance Business Intelligence Consultant at Superprof Germany & Upwork
- Design an interactive Tableau dashboard to analyze historical aviation accidents using data from the Federal Bureau of Aircraft Accident Investigation
- Develop visualizations to provide actionable insights to improve aviation safety measures employing data modeling and transformation techniques
- Develop a Power BI dashboard to monitor sales KPIs and product performance integrating data from multiple sources
- Design a star schema data model and implement advanced DAX measures for high-performance and dynamic reporting
- Design a comprehensive BI architecture solution focusing on ETL pipelines, data integration, and data governance
- Recommend Power BI as the central tool and create a security-compliant implementation roadmap
Roman Krivtsov
Last position:
Senior Data Engineer / Cloud Architect at DB Systel
- Development of a central billing app for cloud costs at DB
- AWS
- Python
- AWS CDK
- RDS
- Spark (PySpark)
- Glue
- Lambda
- CI/CD (GitLab)
- React/Typescript
- data optimization
- Scrum
Delly Fofie
Last position:
Dad of 2 daughters at Family
Pascal Schuster
Last position:
Full-Stack Engineer at Playbook Digital, Inc
- Work in a rapidly moving environment on scalable and performant organizational features for a growing SaaS creative storage & digital asset management startup
- Optimization of data storage and retrieval routines in hot code paths across a containerized microservice architecture
- Implementation of new feature packages in a largely independent and self-sufficient manner, down the stack; design of both backend architecture and frontend UIs in the absence of templates, mock-ups, or other guide rails
- Autodidactic onboarding, rapid learning and subsequent productive application of technologies I was previously fully unfamiliar with (Ruby/Rails)
Petru Kisalita
Last position:
Architect & Technical Team Lead & Senior Developer at Goetel GmbH
- Design, architecture & development/programming of ETL/ELT data pipelines, DWH, BI solution
- Technical project lead, POC – proof-of-concept creation
- Liaison between business units and technical teams
- Azure DevOps Boards & Jira
- Data modeling & data engineering – data warehouse & data mart
- Azure (Data Factory, Azure SQL, Azure DevOps CI/CD, Azure Data Lake V2, Business Central REST API, OData API, OAuth2 tokens)
- SharePoint lists & API for ADF, Firebird DB, Postgres DB, DB2
- Power BI (Power Query), DAX, Excel PBI add-on, GIS data
- Automated ETL process monitoring/logging, performance monitoring, error monitoring – capturing & resolution
- Index performance tuning & statistics monitoring, Transact-SQL
- Data security – MFA (multi-factor authentication) & OAuth2, MS Graph, Azure networks & firewalls, gateways, roles, user groups – with read/write permissions
- Sources – Vario Bill, Camunda, Radius, Geo Database, OTRS, PAST, MS Dynamics Business Central, Azure Blob Data Lake, SharePoint lists
Discover over 15,000 top freelancers
Statistics of experts using Data Pipeline
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 13 years)
Position duration
2.1 years (Germany: 2.8 years)
Positions per freelancer
11 (Germany: 8)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Healthcare
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
67% (Germany: 72%)
Doctorate
13%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
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 Frankfurt 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 Frankfurt using Data Pipeline
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
What it covers
A data pipeline moves data from source systems to the tools that need it. It can pull from apps, databases, logs, APIs, and files, then clean, shape, and load that data for reporting, analytics, or product features. Strong work here keeps data flowing on time and in the right format.
Common work
- Build ETL and ELT flows
- Connect databases, APIs, queues, and file stores
- Schedule jobs and handle retries
- Validate, clean, and transform records
- Prepare data for warehouses and dashboards
Tooling and stack
The stack often includes Apache Airflow, Kafka, Spark, dbt, and cloud services from AWS, Azure, or Google Cloud. Many teams also use Snowflake, BigQuery, or Databricks for storage and processing. Good specialists know when to use batch jobs, event streams, or a mix of both.
When to bring in help
Companies usually look for freelance expertise when a pipeline breaks, slows down, or needs a redesign. That also happens during cloud migrations, new warehouse rollouts, or when source systems change often. In Frankfurt, this is common in finance, logistics, media, and data-heavy internal systems.
What strong specialists do
A strong professional thinks beyond moving rows from one place to another. They care about data quality, lineage, monitoring, idempotency, error handling, and sensible ownership. They write code that is easy to test, easy to operate, and easy to change.
What to look for
- Clear logic for extraction, transformation, and loading
- Experience with orchestration and observability
- Careful handling of schema changes and late data
- Solid SQL and scripting skills
- Calm collaboration with analysts, product teams, and platform experts
Frequently asked questions
Not sure where to start with Data Pipeline? These answers cover the essentials.
A strong data pipeline moves data from source systems into warehouses, lakes, or operational tools. Companies use it for reporting, analytics, alerts, personalization, and other workflows that depend on fresh, trusted data. It is the path that turns raw input into usable output.
Data Pipeline is the broader term. ETL and ELT describe specific ways of moving and transforming data, while a pipeline can also include streaming, validation, orchestration, monitoring, and delivery. Many teams use all three terms together, especially when discussing Apache Airflow, dbt, or Kafka.
A good Data Pipeline specialist usually brings strong SQL, scripting, and cloud skills. Experience with orchestration tools, data modeling, and observability is also valuable. If the work involves streaming, Kafka or similar messaging systems can matter too.
The answer depends on the risk and complexity of the data flow. A simple batch job may need one focused Data Pipeline expert, while a multi-source, business-critical setup needs someone who can design for failure, quality checks, and maintenance. The more source systems and consumers you have, the more important deep experience becomes.
Bring in a Data Pipeline freelancer when you need speed, a redesign, or focused help on a specific problem. That is common for migrations, broken jobs, new reporting layers, or a short burst of architecture work. It is also useful when your internal team knows the business but needs outside delivery capacity.
Yes, most Data Pipeline work can be done remotely if access, documentation, and review paths are clear. In Frankfurt, on-site time can still help when teams need close coordination with security, data owners, or legacy system stakeholders. A hybrid setup is common when the environment is sensitive.
Look for clear design choices, not just tool names. A strong Data Pipeline professional can explain failure handling, data quality checks, backfills, monitoring, and how they keep downstream systems stable. Past work that shows clean logic and maintainable code is usually a good sign.
Frequent job failures, slow loads, missing records, and unclear ownership are common warning signs. If teams argue about whether the issue is in source data, transformations, or scheduling, an experienced Data Pipeline specialist can usually find the fault line quickly. That is especially useful when business reporting depends on the flow.
The average hourly rate of freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects is 89 €, which corresponds to a daily rate of about 716 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects, 100% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects are German (100%), English (100%), and French (30%).
The most common industries among freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects are Information Technology (85%), Banking and Finance (45%), and Healthcare (45%).
The most common business areas among freelancers in Frankfurt, Germany who have used Data Pipeline in their recent projects are Information Technology (100%), Business Intelligence (85%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Data Pipeline
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 
Dusseldorf 
Essen 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
