Data Lake Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Data Lake
Karin Albiez
Last position:
AI Benchmark Engineer | Native language specialist German at Lilt
- Task Engineering: Evaluating Coding Agents.
- Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
- Prompting & Translation: finding failure points where AI does not work, in German.
- Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
- Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
- Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
- Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.
Niko Schmuck
Last position:
Developing Architect, Technical Lead "gridlytics" at HH Energienetze
- Building a data integration platform for high, medium, and low voltage assets for contextual analysis of time series with master data from the SCADA control system (IEC 60870 104), INIS, and SAP.
- Responsibility for the architecture and implementation of the solution, as well as sparring partner for the Product Owner.
- Use of Kotlin, Spring Boot, Maven, TimescaleDB, PostgreSQL, liquibase, Elements IoT, Docker, Kubernetes, Grafana, Python, jupyter, and various API gateways.
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.
Christian Frauer
Last position:
Department Head (Interim) at Municipal utilities and transport company
- Definition and setup of the subject areas
- Building a governance model for the department with the areas of responsibility
- IT strategy, project management, process management, and quality and sustainability management
- Developing a communication strategy within the group
- Creating the IT strategy
- Designing templates, guidelines, and processes for consistent work
- Capturing strategic guardrails and grouping ongoing projects – deriving a roadmap for strategic planning
- Reviewing ongoing projects
- Creating staffing calculations and volume structure
- Defining job profiles
Chisom N.
Last position:
Founder & Analytics Engineer at Museni Nexus
- Client — Podimo ApS (podcast & audiobook streaming): build the finance reporting layer on BigQuery + dbt + Airflow, including the core revenue-transaction fact tables used across finance reporting.
- API automation: design and build a BigQuery → Airflow → Microsoft Dynamics 365 Business Central REST-API pipeline to automate sales-invoice posting, with idempotency and master-data sync between systems.
- Delivery: sole engineer on the engagement — requirements, modelling, orchestration and stakeholder communication with the client finance team, end to end.
Alexander Zhirov
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.
Philipp Grunert
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
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.
Alexander Bromberg
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Prasad Tilloo
Last position:
Solution Architect / Senior Manager – DTC E-Commerce Platform at BRITA
- Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
- Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
- Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
- Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
- Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
- Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
- Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka
Oliver Voss
Last position:
Interim Manager and Business Consultant at Self-employed
- Development of an entry strategy for the claims area of an insurance service provider.
- Analysis and optimization of existing claims processes.
- Definition of management metrics and KPIs to improve performance and efficiency.
- Advising management on market positioning and process digitalization.
- Leading an IT team with 13 employees in a temporary vacancy role.
- Ensuring stable IT operations and managing external IT service providers.
- Leading regulatory projects, especially for the implementation of the DORA regulation.
- Preparation for and support during an IT security audit.
- Change management and conflict moderation in a challenging transformation environment (FI migration).
Jorge Machado
Last position:
Technical Lead / Fractional CTO at Würth GmbH
I designed and developed an AI-powered multi-tenant platform on Azure that transforms SAP process recordings into technical documentation, presentations and automated tests, processing over 15,000 process recordings for enterprise customers like Würth. I owned the architecture, the production releases and the DevOps setup. I also designed a multi-tenant system with SSO and role-based access on Azure. Implemented an MCP Server with Dynamic OAuth Authentication.
Main Tasks:
- Sprint planning and feature preparation
- Design the multi-tenant platform architecture (FastAPI, SQLAlchemy, PostgreSQL row-level security for tenant isolation)
- Develop AI pipelines with Prefect for transcription (Azure Speech API), document generation and SAP screen-recording analysis (Claude, gpt-4-mini)
- Design and implement an MCP server to expose tenant knowledge to LLM clients (Claude), with async retrieval and reranking
- Implement LLM cost tracking, rate limiting and client pooling for Anthropic/OpenAI/Azure OpenAI endpoints
- Set up CI/CD: Docker images to Azure Container Registry, GitHub Actions, Azure Static Web Apps, Alembic migrations in containers
- Manage production releases and execute live data migrations for enterprise customers
- Define engineering standards and architecture patterns for the team
Environment: Azure / Azure Foundry / Python / FastAPI / Prefect / React / PostgreSQL
Maximilian Braun
Last position:
CTO at nikan.ai
Leading the technical vision and product strategy for a sovereign AI startup focused on European data infrastructure and compliance. Managing a cross-functional team of 7 across engineering, AI development, and operations in a fully remote environment.
- Defining the company's product and technology roadmap, including AI-powered solutions with integrated payment services
- Designing scalable platform architectures with emphasis on data sovereignty, security, and European regulatory compliance
- Driving hands-on development across the full stack while establishing engineering best practices and DevOps workflows
- Enabling developer productivity through mentoring, architectural guidance, and tooling decisions
- Shaping the long-term technical strategy to position the company for sustainable growth
Christiane Neher
Last position:
Management Consultant at Christiane Neher Management Consulting
Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:
- Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
- Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
- Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
- Conceptual support for the development of an integrated reporting and performance management setup
- Execution of customer insights analyses to identify patterns and anomalies within customer data clusters
Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:
- Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
- Strategic-operational consulting for the introduction of RELEX including best practices
- Support in defining overarching goals and requirements (2-year target picture)
- Guidance in scoping a relevant supply chain network segment for the project
- Development of a roadmap for iterative, incremental RELEX setup and rollout
- Assessment of project dependencies (interfaces, configurations, etc.)
- Advice on prioritized implementation of business requirements and data interfaces
- Support in test planning (data validation, system testing, UAT)
- Consulting on internationalization, change management, training, and knowledge transfer
- Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX
Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:
- Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
- Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
- Proposal of quality improvements for program and modernization efforts
- Sparring partner and professional, technical, structural and organizational consulting for project and program management
Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:
- Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
- Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
- Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
- MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)
Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:
- Coaching of the core team with topic managers and team leads
- Introduction to the OKR topic and setup of the OKR cycle
- Establishment of the OKR approach in teams and on a cross-team level
Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:
- Analysis of current challenges
- Definition of overarching goals
- Development of a proposal for a new team structure
- Identification of required competencies, skills and responsibilities
- Advisory and alignment on communication and change management strategy
Thomas Hoefkens
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Build and operate an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for the automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, Autoformer).
- Implement CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform), data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) through training and evaluation to model registry and endpoint deployment.
- Integrate MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Develop and containerize PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), log centralization, and cost monitoring.
- Automate infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connect to existing market data systems and event pipelines.
- Migrate existing workloads and databases (IONOS → Azure, MongoDB) with integration into central MLOps workflows and internal networks.
- Extend the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyze and architect a software solution to process large volumes of data efficiently (>3000 messages/sec.) (market data store).
- Spring Boot / Java 21 container development with RabbitMQ for distributing stock market data via MongoDB (Kubernetes) with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integration of RESTHeart to create a REST API for MongoDB.
- Build an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Develop Python scripts for transforming and cleaning incoming stock market data (Pandas, scikit-learn).
Discover over 15,000 top freelancers
Statistics of experts using Data Lake
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
2.4 years
Positions per freelancer
10
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
95%
Master's degree or higher
70%
Doctorate
17%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
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 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 Data Lake
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 a data lake is
A data lake stores raw and processed data in one place, ready for reporting, analytics, and machine learning. It fits structured tables, logs, events, files, and streaming data without forcing one fixed schema first.
Common use cases
- Centralize data from apps, databases, and SaaS tools
- Prepare datasets for BI, forecasting, and model training
- Keep history for audit, replay, and ad hoc analysis
- Support batch loads, event streams, and file drops
Platform stack
Strong specialists work with object storage, catalog tools, and transformation layers around the lake. They often use S3, Azure Data Lake Storage, Google Cloud Storage, Databricks, Spark, dbt, Airflow, and metadata or governance services.
Where companies need help
Teams bring in freelance expertise when a lake grows messy, slow, or hard to trust. That happens during cloud migrations, new data products, platform redesigns, or when source systems in Germany and other regions must feed one shared analytics layer.
What good specialists deliver
Good professionals define folder and table layout, naming rules, access control, and retention patterns. They also set up ingestion, schema handling, quality checks, and documentation so teams can use the lake without guessing where data comes from.
What to look for
- Clear thinking about raw, curated, and trusted zones
- Hands-on work with batch and streaming pipelines
- Practical governance, security, and lineage habits
- Experience with query engines and lake performance tuning
Frequently asked questions
What clients ask us most about Data Lake — answered in short.
A data lake is used to store many kinds of data in one place so teams can analyze it later. Companies use it for reporting, machine learning, historical replay, and central data sharing across departments. It works best when raw data must stay flexible before it is shaped for a specific use.
A data lake keeps data in a more raw form and accepts many file and event types. A data warehouse is usually more structured and optimized for trusted reporting. Many companies use both: the lake for broad intake and exploration, the warehouse for curated business reporting.
Bring in a data lake specialist when ingestion is failing, data quality is unclear, or access rules are messy. Freelance help also makes sense during a cloud migration, a platform rebuild, or when teams need a clean foundation before adding analytics or machine learning. A strong specialist can stabilize the design quickly.
A good data lake expert should also know pipelines, data modeling, and governance. Useful adjacent skills include Spark, Airflow, dbt, SQL, cloud storage, and catalog or lineage tools. Security and cost control matter too, because lakes can become expensive and hard to manage without discipline.
Azure Data Lake is a Microsoft service used to build a data lake on Azure. It is not the only way to create one, but it is a common option for companies already using Microsoft cloud services. Many searchers use the term to mean both the service and the broader architecture.
Ask how the data lake will be organized, who will own quality checks, and how access will be controlled. Also ask which tools they prefer for ingestion, transformation, and governance, and how they document decisions. The best experts explain trade-offs in plain language, not just tool names.
Yes, data lake work is often done remotely because most tasks are design, pipeline, and review work. For companies in Germany, remote collaboration usually works well when the specialist can communicate clearly in English and align with local stakeholders. On-site time helps more during workshops, sensitive migration phases, or when teams want close process alignment.
A strong data lake specialist leaves behind a structure that other teams can actually use. Look for clear zone design, reliable ingestion, documented data contracts, and practical governance. Good work is visible in fewer breakages, easier discovery, and less manual cleanup for the teams that depend on the lake.
The average hourly rate of freelancers in Germany who have used Data Lake in their recent projects is 103 €, which corresponds to a daily rate of about 822 € based on an 8-hour working day.
Of the freelancers in Germany who have used Data Lake in their recent projects, 95% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Germany who have used Data Lake in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Germany who have used Data Lake in their recent projects are German (98%), English (98%), and French (22%).
The most common industries among freelancers in Germany who have used Data Lake in their recent projects are Information Technology (86%), Professional Services (56%), and Banking and Finance (49%).
The most common business areas among freelancers in Germany who have used Data Lake in their recent projects are Information Technology (95%), Business Intelligence (78%), and Product Development (64%).
Main locations of FRATCH Experts, who have recently used Data Lake
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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