ETL Experts
in minutes with vetted specialists and precise AI matchingHire experts who design ETL pipelines, clean and reshape source data, and keep batch and scheduled loads reliable across warehouses, lakes, and BI stacks. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts who have recently used ETL
Ornel Franck Wora Yeno
Last position:
Sales Partner at ERGO PRO
- Industry: Insurance, Trade, IT
- Customers & Projects: Consulting and selling insurance and similar services
- Main tasks: Insurance consulting (health insurance, retirement planning, wealth building); commercial services, inside and field sales; sales data analysis and forecasting; customer consulting and support; opening a new sales headquarters for private and business customers; business development & innovation management; business use case development; process optimization; stakeholder management; team leadership and training; preparation and delivery of trainings;
- Technologies used: Microsoft Office 365, Microsoft Teams, Jira, Draw.IO, Camunda 8, Java (8, 17,21,25), Git, Spring Boot, Spring Batch, Spring Data REST, Spring Web, Spring Security, J-Unit, Playwright, Lombock, Vaadin, H2, PostgreSQL (16, 17 18), pgAdmin, Docker, LLMs, JasperSoft Studio, JasperReports
Kiriakos Krastillis
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.
Peter Schillen
Last position:
Senior ML Engineer & AI Researcher at Anonymous client
Project: Defect generation on inspection images of metal surfaces
Environment:* Automated Visual Inspection (AVI), Metallurgy & Manufacturing
Goal & implementation: Concept, architecture, and training of Generative Adversarial Networks (Pix2PixHD / SPADE) for image-to-image transformation. Targeted generation of synthetic material defects (e.g. cracks, inclusions, scale) on rough metal surfaces under real inspection-light conditions for privacy-compliant and efficient dataset expansion (Data Augmentation).
Technical design: Implementation of robust Generative AI and Computer Vision pipelines in Python and PyTorch. Use of semantic segmentation approaches for mask-guided defect synthesis and downstream evaluation with EfficientDet object detection models.
Business impact: Massive dataset upscaling (factor of 10x) without time- and cost-intensive physical inspection runs, while at the same time drastically improving the detection performance of automated inspection systems.
Technologies & skills used: Python | PyTorch | SPADE | Pix2PixHD | EfficientDet | Machine Learning | Semantic Segmentation | Computer Vision
Collin Kempkes
Last position:
Software Architect / Fullstack Developer at Equity Bytes
Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.
- Designed and operated a highly scalable microservice and serverless architecture
- Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
- Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
- Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
- End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
- Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
- Robust backup and disaster recovery strategies
- RDS Postgres backups and hourly snapshots
- Read-only, asynchronously synchronized replicas with automated master failover in emergencies
- Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
- Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
- Integrated Stripe for international payment processing
- Built a marketplace payment system with multiple parties and payout routines
- Used Algolia for high-performance real-time search of digital assets on the platform
- Federation of services with GraphQL and Hasura
- Later migration to GraphQL Mesh
- Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
- Used Next.js / React for modern frontend applications in the nx monorepo
- Enterprise security architecture & access control
- Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
- Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
- Built internal microfrontends with Retool for fast prototyping and operational business processes
Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest
Jens Henneberg
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilizing an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Fadi Shoaa
Last position:
Development of a production-ready Enterprise Document AI & Recommendation Platform at Freelancer
- Development of a production-ready Enterprise AI solution for the automated processing of invoices and business documents
- Integration of Azure AI Document Intelligence and LLM technologies into existing business processes
- Development of robust REST APIs for automated document processing and system integration
- Extraction, validation, and storage of structured invoice data in Azure SQL as a base for analytics and machine learning models
- Development of an AI-based recommendation engine with machine learning and deep learning to generate personalized product recommendations based on historical purchase data
- Implementation of logging, monitoring, error handling, and validation mechanisms for stable production use
- Collaboration with business teams to define business rules and integrate the solution into existing enterprise processes
Technologies: Python, Azure AI Document Intelligence, Azure OpenAI, Azure SQL Database, REST APIs, Machine Learning, Deep Learning, OCR, Pandas, JSON, Workflow Automation
Christine Tantschinez
Last position:
Communications Consulting at Storytrend
Most mid-sized companies already have their numbers. What is missing is the translation: a dashboard with forty tiles does not answer a single question that is actually asked in management.
Analysis
- Evaluation of existing data with Python and SQL
- Checking data quality and methodology before making a statement
- The result is an analysis that leads toward a concrete decision
Preparation
- Reports in Power BI and Tableau
- Interactive calculators and visualizations on the web
- Presentations and specialist texts for customers, sales and the public
- Analysis and communication from one source — that
Henning Uiterwyk
Last position:
Senior Expert Data Governance, Master Data Quality and Data Migration at E.ON
- Planning and implementation of a migration strategy for master and transaction data for the continuous loading of a cloud-independent database
- Creation and pilot implementation of a company-wide Business Data Model for customers, suppliers, contracts, products, prices, consumption, invoices, and dunning
- Concept and consulting for a Data Governance Framework incl. definition of committees, roles, processes, and metadata model
- Operationalization of the Data Governance Framework with definition of data standards
- Sub-project management in two pilot projects (PoCs) for Data Governance systems (ErwinDIS and Atlan)
- Training and coaching the data team in migration, data quality, and data modeling
Oleg Orlov
Last position:
Senior Software Developer / BI Integration Developer Power BI, C# at Telecommunications
Embedded Analytics & AI-assisted BI
Design and development of an integrated analytics solution based on ASP.NET Core, Power BI Embedded, and LLM services to provide context-based business information.
Development of an AI agent with Function/Tool Calling for the secure orchestration of REST APIs, SQL data sources, and technical services within defined business processes.
Building automated BI workflows including workspace management, deployment processes, and scheduled refresh via the Power BI REST API.
Implementation of secure service-to-service communication with Microsoft Entra ID and Service Principal, and integration into existing enterprise system landscapes.
Technologies: ASP.NET Core, C#/.NET, Power BI Embedded, Power BI REST API, LLM API, AI Agents, Function/Tool Calling, Entra ID
Umut Gülac
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.
Ali Aminian
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Daryoosh Dehestani
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
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.
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management control during a restructuring program (approx. 80 people involved)
- Set up the PMO to enforce transparency, reporting, and data-driven decisions
- Developed an integration template to move team silos (software, field installation, supply chain) into a cross-functional project structure with lean tracking systems for timeline, progress, and KPIs
- Technologies / methods: PMO setup, KPI tracking, project organization, Jira, Confluence
Hervé Teguim
Last position:
Senior Data Engineer at Schweizerische Post AG
Tools: Fabric, AWS, dbt, Power BI, SQL, DWH, R, Python
- Supported customers in implementing an architecture design for extracting and preparing data
- Planned the design and implementation of the BI and DWH platform
- Ensured the scalability and performance of the data platform
Discover over 15,000 top freelancers
Statistics of experts using ETL
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
5.2 years
Positions per freelancer
11
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
95%
Master's degree or higher
66%
Doctorate
11%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
97%
Based on our profile pool as of 6 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology 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 using ETL
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 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What ETL covers
ETL stands for extract, transform, load. It moves data from source systems into a target store where reporting, analytics, and operational teams can use it. Strong ETL work keeps source detail intact while shaping it into a form that is fast to query and easy to trust.
Common delivery work
- Pull data from APIs, databases, files, and event feeds
- Clean, map, deduplicate, and standardize records
- Load curated data into a warehouse or lakehouse
- Build scheduled pipelines and retry logic
- Add checks for completeness, freshness, and schema drift
Tools and stack
ETL professionals usually work with orchestration, SQL, scripting, and data integration tools. Depending on the stack, that can include Airflow, dbt, SSIS, Informatica, Talend, NiFi, Spark, Python, and warehouse-native loaders. Good specialists know how these parts fit together and where to keep logic simple.
When companies bring in help
Companies call in freelance ETL specialists when pipelines break, source systems change, or a reporting stack needs a cleaner design. They also step in for migrations from legacy integration tools, new warehouse rollouts, and one-off backfills after bad data. In Germany, this work is often tied to finance, manufacturing, retail, and logistics data flows.
What strong specialists do
A strong ETL specialist thinks about data quality, lineage, and failure handling before writing the first job. They document mappings, make loads idempotent where possible, and leave clear handoff notes for the team. They also understand when ETL is the right fit and when ELT is a better pattern.
ETL in practice
ETL appears in customer analytics, finance reporting, product usage dashboards, master data synchronization, and compliance exports. It is also used to consolidate data from ERP, CRM, commerce, and support systems. In distributed teams, clear specs and source access matter more than being in the same office.
Frequently asked questions
Need clarity? These are the questions we hear most often about ETL.
ETL is used to extract data from source systems, transform it into a usable shape, and load it into a target store such as a warehouse or lakehouse. Companies use it for reporting, analytics, reconciliation, and shared data models that need consistent rules. It is especially useful when source systems are messy or inconsistent.
ETL transforms data before it reaches the target system, while ELT loads first and transforms inside the destination. ETL is often a better fit when you need strict control over mapping, cleansing, or validation before data lands. ELT can be better when the warehouse has strong compute and the team wants to keep raw data available.
A strong ETL specialist usually brings solid SQL, data modeling, scripting, and an understanding of orchestration and scheduling. Experience with APIs, file formats, cloud storage, and warehouse platforms also helps. Clear documentation and careful testing are just as important as tool knowledge.
ETL work needs enough context to understand source systems, business rules, target tables, and data quality expectations. A small fix may only need access to the pipeline and error logs, while a redesign needs mapping rules, sample data, and stakeholder input. The clearer the source-to-target flow, the faster a specialist can deliver.
Most ETL work can be done remotely because it relies on access to systems, data samples, and clear requirements rather than physical presence. On-site time can help when source owners, analysts, and operations teams need to align on data definitions or a migration plan. For many projects, a mix of remote delivery and short workshops works best.
A strong ETL implementation is predictable, testable, and easy to support. Look for clear mappings, idempotent loads where possible, error handling, logging, and checks for freshness and completeness. Good specialists also explain trade-offs and can show how they handle schema changes.
ETL is a better choice when the same logic must be reused across many reports or systems, or when source data needs cleaning before anyone trusts it. It reduces duplication and keeps business rules in one place. Raw queries can be fine for quick analysis, but they are harder to govern at scale.
They are often looking for ETL specialists who can move and shape data across systems, even if they use different tools. Search terms like data integration, Informatica, Talend, SSIS, or Airflow often point to the same kind of delivery work. The exact tool matters less than the ability to build reliable pipelines and maintain them over time.
The average hourly rate of freelancers who have used ETL in their recent projects is 98 €, which corresponds to a daily rate of about 783 € based on an 8-hour working day.
Of the freelancers who have used ETL in their recent projects, 95% hold at least a Bachelor's degree, 66% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers who have used ETL in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 5.2 years.
The most common languages among freelancers who have used ETL in their recent projects are German (98%), English (97%), and French (18%).
The most common industries among freelancers who have used ETL in their recent projects are Information Technology (86%), Banking and Finance (43%), and Professional Services (42%).
The most common business areas among freelancers who have used ETL in their recent projects are Information Technology (97%), Business Intelligence (84%), and Product Development (69%).
Main locations of FRATCH Experts, who have recently used ETL
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.
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