
Data Lake Experts in Germany
matched in minutes by AIHire experts who design scalable storage architectures, build reliable ingestion pipelines and prepare data for analytics, machine learning and reporting. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Germany, who have recently used Data Lake
Oliver V.
Last position:
Interim Manager and Management Consultant at Self-employed
- Developed a market entry strategy for the claims division of an insurance services provider.
- Analyzed and optimized existing claims processes.
- Defined management metrics and KPIs to improve performance and efficiency.
- Advised management on market positioning and process digitalization.
- Led an IT team of 13 employees as part of an interim vacancy cover.
- Ensured stable IT operations and managed external IT service providers.
- Led regulatory projects, particularly the implementation of the DORA regulation.
- Prepared and supported an IT security audit.
- Change management and conflict moderation in a challenging transformation environment (FI migration).
Karin A.
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 S.
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.
Christian F.
Last position:
Department Head (Interim) at Municipal utilities and transport company
- Defined and established the areas of responsibility
- Built a governance model for the department and its areas of responsibility
- IT strategy, project management, process management, and quality and sustainability management
- Developed a communications strategy for the group
- Created the IT strategy
- Designed templates, guidelines, and processes for consistent ways of working
- Recorded strategic guidelines and grouped ongoing projects – derived a roadmap for strategic planning
- Reviewed ongoing projects
- Prepared staffing calculations and capacity planning
- Defined job profiles
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management steering during a restructuring program (approx. 80 participants)
- Set up a PMO to ensure transparency, reporting and data-driven decisions
- Created an integration template to transfer team s...
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Philipp G.
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 K.
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 B.
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
Samuel K.
Last position:
Founder & Agentic AI Engineer at Agentakt LLC
Independent engineering practice focused on custom AI systems, production delivery, and fractional technical leadership.
Selected client engagement: Scalutions
Role: Serve as fractional CTO and hands-on technical lead, responsible for the architecture and agentic infrastructure behind its managed B2B outbound operation.
Product: Designed and built OutboundLoop, an agentic SDR operating system for research, qualification, personalized outreach, campaign management, human approvals, measurement, and continuous improvement.
Scope: Own the full system lifecycle—from business processes and agent behavior to context design, model routing, integrations, evaluation, telemetry, reliability, cost control, and production operations.
Prasad T.
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
Maximilian B.
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
Nisanthan S.
Last position:
Business Intelligence Consultant (freelance) at NBIC – Nisanthan BI Consulting
Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)
5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models
Proposal and feasibility assessments for BI and reporting projects
Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development
Custom ERP system
Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.
Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.
Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.
Timesheet app
Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.
Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.
Cash-flow modelling
Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.
Implementation: Built and extended the CF model to include project-development cash flows.
Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.
Jorge M.
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
Lino G.
Last position:
Senior Data Scientist at VinFast Germany GmbH
- Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
- Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
- Automated extraction and training processes with CI/CD
- Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
- Developed and optimized embedded software for automotive control units
- Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
- Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
- Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
- Developed and trained machine learning models using PyTorch
- Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
- Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
- Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
- Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
- Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)
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
18%

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
97%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Discover detailed Data Lake rate benchmarks:
Explore rate insightsAverage 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Lake experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (86%)
- Professional Services (53%)
- Banking and Finance (48%)
- Automotive (35%)
- Transportation (34%)
- Energy (32%)
- Retail (31%)
- Insurance (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What a Data Lake does
A Data Lake stores raw structured, semi-structured and unstructured data in its original form. It gives teams a central foundation for analytics, machine learning, reporting and operational insight without forcing every source into one rigid schema first. Storage commonly uses object stores such as Amazon S3, Azure Data Lake Storage or Google Cloud Storage.
Core architecture
A reliable Data Lake separates ingestion, storage, processing, governance and consumption. Experts define zones for raw, prepared and curated data, then establish formats, schemas, partitioning and retention rules. They also design access controls, metadata management and lineage so the environment remains useful as data volumes, sources and teams change.
Ecosystem and tooling
The surrounding stack depends on the cloud provider and workload. Common components include Apache Spark, Apache Kafka, Apache Flink, dbt, Delta Lake, Apache Iceberg, Trino and orchestration tools such as Apache Airflow.
- Connect databases, applications, files and event streams
- Transform data with batch and streaming pipelines
- Add catalogues, quality checks and lineage
- Serve trusted datasets to BI and machine learning tools
When companies need expertise
Companies often bring in freelance specialists when a growing warehouse can no longer handle every use case, when scattered storage prevents reliable analysis or when a cloud migration needs a clear target architecture. A Data Lake project may also support predictive models, IoT streams, customer analytics or regulatory reporting. In Germany, remote collaboration is common, while on-site workshops can help align data owners, security teams and business stakeholders.
- Define a migration plan from warehouses or file shares
- Repair slow, fragile or duplicated pipelines
- Introduce a lakehouse layer for governed analytics
- Prepare data products for analysts and data science teams
Data Lake versus alternatives
A traditional data warehouse applies structure before data is stored and remains strong for consistent, governed reporting. A Data Lake keeps more source detail and supports varied workloads, but it needs stronger discipline around quality, ownership and discoverability. A data lakehouse combines lake flexibility with warehouse-style tables, transactions and governance through technologies such as Delta Lake or Apache Iceberg.
What strong professionals deliver
Strong Data Lake professionals connect architecture decisions to business outcomes. They can evaluate cloud storage, networking, identity and cost controls while also working hands-on with ingestion, transformation and observability. Look for clear data contracts, repeatable infrastructure, automated tests, documented lineage and a practical plan for operating the environment after delivery. Experience with German teams may also include clear English communication and, where needed, German-language workshops.
Frequently asked questions
What clients ask us most about Data Lake — answered in short.
A Data Lake is used to collect raw data from databases, applications, files, sensors and event streams in one scalable environment. Teams can then prepare it for analytics, machine learning, dashboards, reporting or later data products.
A Data Lake usually stores data in its original form and supports many formats and workloads. A data warehouse applies more structure before analysis, which can make governed reporting simpler but less flexible for new or unstructured sources.
A Data Lake is a good fit when broad, low-cost storage and flexible exploration are priorities. A data lakehouse adds table management, transactions and stronger analytical controls, so the choice depends on governance needs, workload complexity and the existing cloud stack.
A strong Data Lake specialist often works with cloud object storage, Apache Spark, Kafka, SQL, orchestration, infrastructure as code and data quality tooling. Knowledge of identity management, catalogues, lineage, observability and machine learning workflows is also valuable.
A Data Lake engagement needs enough experience to cover architecture, ingestion, security, governance and operations rather than storage alone. The right level depends on whether the work is a focused pipeline, a migration, a lakehouse design or a company-wide data foundation.
Yes, Data Lake work is often suitable for remote collaboration because environments, pipelines and documentation are managed online. On-site sessions in Germany can still help with architecture workshops, access reviews and alignment between business and data teams, while language expectations should be agreed early.
A well-built Data Lake has documented ownership, lineage, access rules, quality checks, monitoring and repeatable deployment. Ask the specialist to explain how failures are detected, how data is discovered, how schemas change and how the environment is kept usable over time.
A Data Lake can become a disorganized storage area when teams skip ownership, metadata, quality controls and lifecycle rules. Weak partitioning, uncontrolled access and unclear retention can also increase operating costs and reduce trust in the data.
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 827 € 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 18% 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 (97%), English (97%), and French (19%).
The most common industries among freelancers in Germany who have used Data Lake in their recent projects are Information Technology (86%), Professional Services (53%), and Banking and Finance (48%).
The most common business areas among freelancers in Germany who have used Data Lake in their recent projects are Information Technology (96%), Business Intelligence (78%), and Product Development (66%).
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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