Data Pipeline Experts in Munich
in minutes from vetted specialists with the power of AIHire experts who design reliable data flows, build ETL and ELT jobs, and connect batch and streaming sources with warehouse and lake targets. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Data Pipeline
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Ajay Kumar Deekonda
Last position:
Senior BI and Analytics Engineer at Novartis
- Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
- Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
- Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
- Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
- Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
- Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
- Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
- Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
- Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.
Tamás Eppel
Last position:
Senior Software Developer / Tech Lead at NDA (defense / OSINT)
- Designing the audit logging framework
- Implementing APIs for developers to integrate in their codebase
- Implementing ingestion pipeline, database query layer and UI for browsing the audit events
- Improving stability and reliability of the backend system
Mirza Klimenta
Last position:
Agentic AI for a DeepResearch project at Freelance
- Created a multi-agentic system supported by a knowledge graph to automate drafting of research papers
- Used multiple experts (OpenAI models) collaborating during document drafting
- Extracted useful information from the knowledge graph
- Technologies: LangChain, LangGraph, Smolagents, LlamaIndex, dspy
- Infrastructure: Terraform and GitHub Actions (CI/CD) on AWS
- Deployed initial application as a Streamlit app
Damian Åšniatecki
Last position:
CTO at FRATCH.IO
- Managed end-to-end product development, overseeing the successful delivery of technical solutions.
- Led and mentored a team of highly specialised technical professionals, fostering a culture of collaboration and innovation.
- Oversaw the hiring process to build a talented and dedicated team.
- Built a scalable and robust backend microservices system from scratch, designing and extending it to meet evolving business needs.
- Ensured the system's high availability with a 99.99% up time, implementing resilient architecture and monitoring mechanisms.
- Developed and implemented technical strategies, aligning them with business goals and objectives.
Suyash Shaha
Last position:
Data Analyst - Reporting & Analytics at SIXT SE
- Developed & maintained customer analytical reporting solutions to identify revenue trends, performance drivers, risks & optimization opportunities to ensure data driven decision making across Sales, Finance, Product, Data Engineering & Controlling.
- Defined & analyzed customer trends & performance metrics to identify root causes behind variances, anomalies & emerging risks across business domains to deliver actionable recommendations.
- Developed & owned analytical data models & reporting layers to ensure scalability, performance & analytical robustness to support executive & operational reporting across business domains.
- Planned, tracked & executed projects by ensuring adherence to timelines, data accuracy, consistency, deliverables, reliability & data quality standards through rigorous validation & reconciliation processes.
- Raised the analytical maturity by formalizing analytical workflows, documenting data processes & standard operating procedures (SOPs) & conducting training sessions to drive adoption of self-service analytics & embed a data driven culture across operational and business teams.
- Took ownership of the end-to-end lifecycle roadmap from requirement gathering, collection, transformation, developing robust business logics to data storytelling & stakeholder delivery.
- Converted complexity into structured clarity by translating requirements & business processes into analytical recommendations to ensure alignment between non-technical & technical stakeholders.
- Conducted advanced SQL based analysis of complex business datasets to uncover trends, correlations & performance improvement opportunities.
- Drove process automation & efficiency improvements by leveraging Python, SQL optimization & AI assisted tools to reduce processing time & increase reliability across analytical & operational workflows.
- Standardized KPI definitions & reporting logic to ensure consistency & trust across reporting solutions.
- Developed process monitoring dashboards & analyses to identify inefficiencies, bottlenecks & compliance deviations across end-to-end business processes to derive actionable recommendations for process improvement & automation.
Srinivasu Kakaraparti
Last position:
Atruvia
Project: Tax Exemption Order Application
The client has an existing application for creating and maintaining tax exemption orders for end customers; design and implementation of a comparable application for internal employees.
- Design and implementation of microservices and the UI for the business area "tax exemption orders" using Domain Driven Design as well as Spring Boot and Angular.
- Implementation of reactive, non-reactive, and asynchronous APIs (Spring REST, WebFlux, GraphQL).
- Development of the Angular application, including state management using Signals, RxJS Observables, and subscriptions.
- Securing the API and the application using OAuth2, JWT, and OpenID Connect.
- Configuration and setup of CI/CD pipelines with Jenkins.
- Collaboration with cross-functional teams and conducting code reviews.
Environment: Java, Spring Boot, Angular 18 & 19 (standalone, signals), RxJs, Bootstrap CSS, Vitesting, OpenShift, Istio, microservices, Kafka, Dynatrace, Jenkins, GitLab, Graylog, Sonar, Oauth2, OracleDB
Any-Arlene Niyubahwe
Last position:
Co-Founder · Data Engineering & Backend at zirikana (Kirundi Bible Web App) – Civic Technology
- Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
- Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
- Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
- Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.
Tapasvi Mishra
Last position:
Data Analyst — Working Student at DENSO Automotive Deutschland GmbH
- Built and maintained Power BI dashboards (DAX, Power Query, data modeling) tracking KPIs across 15+ global manufacturing sites — primary reporting tool for EU leadership decision-making.
- Developed a multi-screen Power Apps application (configurator-style tool) with SharePoint-based workflow integration for the sales team — designed jointly with business stakeholders and IT.
- Built and maintained automated Power Automate workflows connecting to SQL databases; independently identified and deployed an LLM-driven automation use case that eliminated 90% of manual reporting effort — self-pitched to leadership and taken end-to-end into production.
- Built a Python-based data pipeline (SQL) extracting, modeling, and validating data across 10+ EU plants — establishing reliable data models and KPIs for cross-site reporting.
Serge Kalinin
Last position:
MLOps (machine learning operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
Anitha Namineni
Last position:
Senior Data Engineer at Accenture GmbH
- Designed, developed, and configured scalable data applications aligned with business processes and technical requirements.
- Architected scalable, cost-effective data architectures leveraging Snowflake across AWS, Azure and GCP, integrating dbt for data transformation and modeling.
- Built and maintained robust ETL Data Pipelines, ensuring high data quality for seamless migration and cross-system integration.
- Demonstrated strong expertise in SQL & Python with extensive experience in data modeling, ETL/ELT pipeline development, and streaming data processing; proficient in Git-based version control, CI/CD practices, and testing frameworks, with solid knowledge of data quality, observability, cost optimization, security, and data governance principles.
- Led multiple data migration initiatives from SAP HANA to Snowflake using a modular dbt framework.
- Designed and maintained end-to-end data transformation workflows using dbt on Snowflake, implemented layered data models, optimized performance, and ensured high-quality data delivery for business intelligence and reporting.
- Managed development, QA, and production deployments through structured version control and release management using GitLab.
- Integrated and centralized data from multiple sources including relational databases, flat files, Excel, and large-scale systems into Snowflake.
- Applied strong expertise in Sales, Marketing, HR, and ERP data domains, developing and maintaining relevant KPIs and reporting solutions.
- Collaborated with cross-functional teams to deliver end-to-end data solutions on schedule through proactive issue resolution and effective coordination.
- Administered the Snowflake sandbox environment for Data Engineering division.
- Trained colleagues transitioning into data roles on Snowflake and provided technical guidance and mentorship to junior team members.
Manikanta Rangaswamy
Last position:
Data Engineer at Insurance client
- Design, development, and maintenance of end-to-end ETL pipelines for scalable and reliable data integration
- Support in data quality checks, testing, and migrations
- Development and maintenance of dbt models for structured, modular, and reusable data transformations
- Use of AI-driven development to improve ETL job creation and code quality.
- Development of CI/CD for automated deployment.
Hardeep Bhutter
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.
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Worked out measures to improve management control during a restructuring program (approx. 80 people involved)
- Set up PMO to enforce transparency, reporting, and data-driven decisions
- Built an integration template to move team silos (software, field installation, supply chain) into an overarching project structure with lean tracking systems for timeline, progress, and KPIs
- Technologies / methods: PMO setup, KPI tracking, project organization, Jira, Confluence
Alexandre Savio
Last position:
Cloud Engineer at Dectris AG
- Build a scalable multi-region backend service in AWS to serve remote desktop virtual machines for scientific analysis
- Stack: AWS, GitHub, Terraform, Python, Rust
- Built and defined the core infrastructure of the backend system
- Defined and coded the virtual machines provisioning supporting Ubuntu and Rocky Linux desktop setups
- Programmed the API service running in ECS to manage virtual machines and build custom Docker images for users
Discover over 15,000 top freelancers
Statistics of experts using Data Pipeline
Aggregated from the professional profiles of matched freelancers.
Experience
12 years (Germany: 13 years)
Position duration
1.9 years (Germany: 2.8 years)
Positions per freelancer
7 (Germany: 8)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
70% (Germany: 72%)
Doctorate
16% (Germany: 13%)
Certifications per freelancer
3
Most common languages
English, German, Spanish
Speak two or more languages
97% (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 Munich 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 Munich 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
Data flow
Data pipelines move data from source systems to the tools where teams analyze it, report on it, or trigger actions. Strong specialists keep that flow stable, traceable, and easy to change as business needs shift.
Common work
- ETL and ELT jobs for warehouses and lakes
- Batch and streaming ingestion
- Data cleansing, enrichment, and validation
- Orchestration, scheduling, and retries
- Monitoring, logging, and alerting
Typical stack
Many projects use Apache Airflow, Kafka, dbt, Spark, Snowflake, BigQuery, or Databricks. Skilled professionals know when to use each part, how to connect them, and how to keep data models and handoffs simple.
When to bring help
Companies bring in freelance expertise when pipelines fail, grow too hard to maintain, or need a faster path to production. In Munich, this often fits teams working with analytics, manufacturing data, mobility, finance, or connected products, where dependable data movement matters every day.
What good specialists do
- Design clear source-to-target flows
- Handle schema changes without breaking downstream use
- Reduce latency and duplicate records
- Build tests for freshness, completeness, and quality
- Document ownership and recovery steps
Signs you need an expert
If teams argue about where data comes from, reports disagree, or manual exports keep growing, the pipeline layer needs attention. A strong Data Pipeline expert finds weak points fast, removes hidden coupling, and leaves a setup your team can operate with confidence.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Data Pipeline.
A strong Data Pipeline expert builds the paths that move data from apps, files, APIs, and event streams into warehouses, lakes, or operational systems. That often includes ETL or ELT jobs, orchestration, validation, and failure recovery. The goal is not just movement, but trusted data that arrives on time and in the right shape.
Data Pipeline is the broader term. ETL and ELT describe common patterns inside that work, while a pipeline can also include streaming, scheduling, monitoring, and data quality checks. Companies often use the terms interchangeably, but a specialist should understand the full flow, not only the transform step.
A Data Pipeline project often uses Apache Airflow for orchestration, Kafka for event streaming, dbt for transforms, and Spark for larger processing jobs. Warehouses and lakehouse tools such as Snowflake, BigQuery, Databricks, or similar systems are also common. The right expert knows how these tools fit together and where they create operational risk.
A good Data Pipeline specialist usually also understands SQL, data modeling, cloud services, and observability. For streaming work, event-driven design and message handling matter as well. For batch work, strong testing, scheduling discipline, and recovery planning are key.
Simple ingestion or cleanup work may need only focused help, but critical pipelines need someone who has handled real production failures. A Data Pipeline expert should be able to explain tradeoffs around latency, cost, data quality, and maintainability. If the pipeline feeds core reporting or product decisions, choose someone who has shipped and supported similar systems before.
Yes. Most Data Pipeline work can be done remotely if the team shares access to source systems, logs, and deployment tools. On-site time in Munich can still help when the work involves local stakeholders, sensitive data, or close alignment with analytics and operations teams.
Look for clear thinking, not just tool names. A strong Data Pipeline professional explains lineage, retry logic, schema handling, testing, and monitoring in plain language. Good signs include clean documentation, simple design choices, and a plan for how the pipeline will be operated after handover.
A careful Data Pipeline freelancer will ask where the data comes from, how fresh it must be, who owns each source, and what happens when a job fails. They should also ask about privacy, access, SLAs, and downstream consumers. Those answers shape the design more than the tool choice does.
The average hourly rate of freelancers in Munich, Germany who have used Data Pipeline in their recent projects is 96 €, which corresponds to a daily rate of about 768 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Data Pipeline in their recent projects, 100% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 16% hold a doctorate.
On average, freelancers in Munich, Germany who have used Data Pipeline in their recent projects have 12 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Munich, Germany who have used Data Pipeline in their recent projects are English (100%), German (92%), and Spanish (10%).
The most common industries among freelancers in Munich, Germany who have used Data Pipeline in their recent projects are Information Technology (72%), Automotive (44%), and Banking and Finance (44%).
The most common business areas among freelancers in Munich, Germany who have used Data Pipeline in their recent projects are Information Technology (90%), Business Intelligence (85%), and Product Development (62%).
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 
Cologne 
Frankfurt 
Dusseldorf 
Essen 
Nuremberg Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
