Skip to main content
🇩🇪GDPR-compliant
Find the right

Data Lake Experts in Munich

for scalable analytics, matched in minutes with vetted professionals

Hire experts who design cloud data platforms, build reliable ingestion pipelines and enable governed analytics across Spark, Delta Lake and modern warehouse tools. FRATCH matches you quickly and precisely with vetted, available freelancers.

Meet FRATCH Experts in Munich, who have recently used Data Lake

Verified expert

Philipp G.

View profile

Machine Learning & Data Engineer

München
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
Verified expert

Christiane N.

View profile

Management Consultant

Munich
Christiane N.

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
Verified expert

Thomas H.

View profile

Senior MLOps, DevOps Engineer

Munich
Thomas H.

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).
Verified expert

Hardeep B.

View profile

Sr. Data Engineer

Munich
Hardeep B.

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.
Verified expert

Harald L.

View profile

Project Management

Grünwald
Harald L.

Last position:

Project Management at Loocid LLC

  • Conducted a comprehensive due diligence review for a potential acquisition of a Swiss manufacturing company as part of a pre-merger analysis
  • Assessed production capacities and technical infrastructure
  • Evaluated integration possibilities into existing business processes
  • Performed risk assessment and developed recommendations for action
  • Documented the findings and presented them to management
Verified expert

Alyosh A.

View profile

Business Intelligence Consultant

München
Alyosh A.

Last position:

Business Intelligence Consultant at Large Private Equity Group

  • Business intelligence and KPI specification and playbook for 35 European companies.
Verified expert

Stephan S.

View profile

Senior Data/ML Consultant & Technical Lead

München
Stephan S.

Last position:

Senior Data/ML Consultant & Technical Lead at Jolin.io

  • Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)

  • Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)

  • Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)

  • Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)

  • Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)

Verified expert

Bhanu A.

View profile

Freelance Salesforce CRM and Marketing Cloud Expert

Munich
Bhanu A.

Last position:

Freelance Salesforce CRM and Marketing Cloud Expert at Arkplus

  • Engage with stakeholders across departments to identify and document business needs, goals, and objectives.
  • Conduct interviews, workshops, and surveys to gather comprehensive requirements for Salesforce solutions.
  • Configure Salesforce products such as Sales Cloud, Service Cloud, Marketing Cloud, Health Cloud, and Data Cloud to align with the company's requirements.
  • Analyze existing business processes and identify opportunities for improvement and automation within the Salesforce platform.
  • Build campaigns, automation and journeys, data management, API and integrations, scripting and customization, analytics and reporting, introduction of generative AI capabilities.
  • Develop custom applications using Apex, Visualforce, and Lightning Components; create and customize Salesforce objects, workflows, validation rules, and triggers; implement custom user interfaces using Lightning Web Components (LWC).
  • Develop training materials and conduct training sessions to ensure effective user adoption of Salesforce solutions.
  • Provide ongoing support to end-users, addressing issues and ensuring they are proficient in using Salesforce tools.
  • Create and execute test plans, including unit testing, integration testing, and user acceptance testing (UAT).
  • Identify and resolve issues, ensuring that Salesforce solutions meet business requirements and quality standards.
  • Design and implement customized reports and dashboards to provide actionable insights and support data-driven decision-making and product delivery.
Verified expert

Nikolay T.

View profile

Senior Cloud Data Architect

Unterhaching
Nikolay T.

Last position:

Senior Cloud Data Architect at Cloudreach/Eviden (an ATOS Company)

  • Architected a self-service Google Kubernetes Engine (GKE) platform for a major financial institution (Commerzbank), enabling 1000+ users across hundreds of product teams to autonomously provision resources and significantly accelerate development cycles.
  • Designed a data-product-oriented platform architecture for the UK Department for Transport (DfT) to serve over 1500 direct end-users and numerous connected third-party systems, enhancing data accessibility and governance.
  • Drove business growth by developing the strategic roadmap for the 'One Cloud' business line, targeting a 10% revenue increase.
  • Served as a key member of the CTO Authority, providing strategic guidance on internal cloud initiatives and best practices.
Verified expert

Maziyar K.

View profile

Senior Data Engineer

Taufkirchen
Maziyar K.

Last position:

Data Engineer at MSD Germany

  • Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
  • Performance Optimization of Data Ingestion of ETL Pipeline
  • Development of Data Validation using Great Expectations
  • Leading of the data migration for two sources exchanges
  • Data Modeling in AWS Redshift

MLOps

  • Model inference implementation by mlflow and AWS SageMaker
  • Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
  • Implementatino of Model Registry and artifactory using mlflow
  • Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
  • Feature importance using mlflow

Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy

Verified expert

Velika I.

View profile

Senior Program Manager - Data Enablement, Client Experience Office

München
Velika I.

Last position:

Senior Program Manager - Data Enablement, Client Experience Office at Sun Life Financial

  • Managed a $30M digital portfolio, integrating strategic goals with technological solutions to personalize and enhance customer experience across business units, increasing engagement and satisfaction.
  • Collaborated with client experience office leadership and cross-functional teams to define business value, driving digital transformation initiatives and digital practices organization-wide.
  • Championed the "Unified View of the Client (UC360)" initiative by leading four agile squads to integrate disparate client data across business units into a single analytics platform, expanding client insights, marketing engagement, and journey analytics.
  • Managed an $8M annual budget, promoting adherence to a +/- 5% budget variance, and conducted quarterly incremental planning to synchronize cross-team dependencies.
  • Drove a $26M increase in sales and retained assets by utilizing UC360 platform to implement targeted marketing strategies and client outreach, facilitated by predictive models and deep insights, boosting analytics team productivity and speeding up market delivery.
  • Resolved misalignments and data inconsistencies by coordinating a third-party assessment to define a new data and analytics target state and operating model, including a governance framework, enabling timely project completion and cross-functional collaboration.
  • Administered detailed reporting on key performance indicators (KPIs), financial forecasting, and resource planning for five agile teams, ensuring projects met objectives and generated quantifiable returns on investment, maximizing efficiency and impact across key business areas.
Verified expert

Natalia D.

View profile

Senior HR BP for Tech and Marketing

Munich
Natalia D.

Last position:

Senior HR BP for Tech and Marketing at KONUX GmbH

  • Org design & HR transformation project.
  • OKRs development.
Verified expert

Daniel C.

View profile

Founder & Managing Director

München
Daniel C.

Last position:

Founder & Managing Director at BotCraft GmbH

  • Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
  • Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
  • Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
  • Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
  • Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Verified expert

Jonas A.

View profile

Senior Consultant (Freelance)

München
Jonas A.

Last position:

Senior Consultant (Freelance) at Various companies in the energy, statutory health insurance (GKV), and IT sectors

  • Consulting in IT sourcing, tendering procedures, and process management
  • Drafting procedure and contract documents
  • Project and document management as well as quality assurance
  • Analysis and optimization of business processes
  • Conflict analysis, contract review, and solution development

Discover over 15,000 top freelancers

Statistics of experts using Data Lake

Aggregated from the professional profiles of matched freelancers.

Experience

20 years (Germany: 18 years)

Data Lake experts in Munich have 20 years of professional experience on average. It is 2 years more than in Germany, where the average stands at 18 years.

Position duration

3.4 years (Germany: 2.4 years)

Data Lake experts in Munich stay in a single position for 3.4 years on average. It is 1 year more than in Germany, where the average stands at 2.4 years.

Positions per freelancer

8 (Germany: 10)

Data Lake experts in Munich have completed 8 positions on average over the course of their careers. It is 2 fewer than in Germany, where the average stands at 10.

Top business areas

Information Technology, Business Intelligence, Project Management

Data Lake experts in Munich have gathered most of their hands-on project experience in Information Technology, Business Intelligence, and Project Management.

Top industries

Information Technology, Banking and Finance, Professional Services

Data Lake experts in Munich are most in demand in Information Technology, Banking and Finance, and Professional Services.

Certification focus areas

Information Technology, Business Intelligence, Project Management

Data Lake experts in Munich earn their certifications most often in Information Technology, Business Intelligence, and Project Management.

Bachelor's degree or higher

89% (Germany: 95%)

89% of Data Lake experts in Munich hold at least a Bachelor's degree. It is 6% lower than in Germany, where the rate stands at 95%.

Master's degree or higher

63% (Germany: 70%)

63% of Data Lake experts in Munich hold at least a Master's degree. It is 7% lower than in Germany, where the rate stands at 70%.

Doctorate

11% (Germany: 18%)

11% of Data Lake experts in Munich have a doctorate (PhD). It is 7% lower than in Germany, where the rate stands at 18%.

Certifications per freelancer

2 (Germany: 3)

Data Lake experts in Munich hold 2 professional certifications on average. It is 1 fewer than in Germany, where the average stands at 3.

Most common languages

English, German, Spanish

Data Lake experts in Munich most often speak English, German, and Spanish.

Speak two or more languages

95% (Germany: 97%)

95% of Data Lake experts in Munich speak two or more languages. It is 2% lower than in Germany, where the rate stands at 97%.

Based on our profile pool as of 19 Sep 2026.

Daily rate distribution

0 3 6 9 12
3 of the Data Lake experts in Munich charge less than €640 per day.
2 of the Data Lake experts in Munich charge between €640 and €800 per day.
8 of the Data Lake experts in Munich charge between €800 and €960 per day.
4 of the Data Lake experts in Munich charge between €960 and €1120 per day.
One of the Data Lake experts in Munich charges €1120 or more per day.
<€640 €640-​800 €800-​960 €960-​1120 €1120+

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 Lake

Rates are based on recent contracts and do not include FRATCH margin.

1000
750
500
250
Rate comparison chart
Daily rate avg. 825 €
Germany avg. 827 €

The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.

1000
750
500
250
Rate comparison chart
Median rate 800 €
Germany median 800 €

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 (80%)
  • Banking and Finance (60%)
  • Professional Services (60%)
  • Insurance (40%)
  • Manufacturing (40%)
  • Telecommunication (40%)
  • Automotive (35%)
  • Transportation (35%)

Please note that freelancers can work across multiple industries, so percentages overlap.

About the technology

What a Data Lake does

A data lake stores structured, semi-structured and unstructured data in its original form, usually on scalable cloud object storage. It creates a central foundation for analytics, machine learning, reporting and data products without forcing every source into one rigid schema. Strong design separates raw, refined and curated data so teams can trust what they use.

Core architecture

A reliable data lake combines storage, metadata, governance, processing and access controls. Professionals select patterns such as medallion architecture and bring together services like Amazon S3, Azure Data Lake Storage or Google Cloud Storage with catalogs, orchestration and observability. They also define ownership, retention, lineage and recovery practices before workloads reach production.

Ecosystem and tooling

  • Build ingestion with Kafka, Debezium, APIs, batch files and change data capture
  • Process and transform data with Apache Spark, SQL, dbt or managed cloud services
  • Organize tables with Delta Lake, Apache Iceberg or Apache Hudi
  • Query lake data through Trino, Presto, Athena, BigQuery or Synapse
  • Connect catalog, quality, security and lineage tools to daily operations

The right stack depends on data volume, latency, compliance needs and existing cloud commitments. Experienced specialists keep formats and interfaces open enough to avoid unnecessary platform lock-in.

When companies need specialists

Companies often bring in freelance Data Lake professionals during a migration, cloud adoption or analytics modernization programme. They can establish a target architecture, repair unreliable pipelines, control rising storage complexity or prepare data for machine learning. In Munich, this work may support manufacturing, mobility, insurance, life sciences and software teams, with delivery organized on-site, remotely or in a hybrid model.

  • Source systems cannot provide consistent, documented data
  • Analysts copy files manually or rely on uncontrolled extracts
  • Pipelines fail without clear ownership and monitoring
  • Access rules, lineage or retention requirements are unclear

What strong professionals deliver

A capable specialist goes beyond loading files. They define partitioning, file sizing, schema evolution, idempotent processing and data-quality checks, then make those decisions visible through documentation and tests. They understand IAM, encryption, networking, cost controls and infrastructure automation, and can explain trade-offs to both technical and business stakeholders.

How to assess project fit

Ask for examples of production data lakes with comparable sources, query patterns and governance demands. Review how the professional handled late data, duplicate records, changing schemas, failed jobs and sensitive information. For Munich-based teams, clear English communication may be enough for an international project, while German can help when workshops involve local operations or business users. A good engagement ends with repeatable pipelines, useful documentation, measurable ownership and a platform the internal team can operate.

Published on:
FRATCH GPT

FRATCH GPT delivers freelancer proposals with clear reasoning and transparent pricing in minutes, helping your hiring department quickly and compliantly find the best talent.

Give it a try:

Try FRATCH GPT

Frequently asked questions

Key details about Data Lake, drawn from the questions we get asked most.

A Data Lake stores data from operational systems, applications, devices and external sources for analytics, reporting and machine learning. It is useful when a company needs to retain varied data first and apply structure as different use cases emerge.

A Data Lake usually keeps data in raw or lightly processed form on scalable object storage, while a data warehouse focuses on curated, structured data for consistent reporting. Many companies use both, with the lake supporting exploration and the warehouse serving governed business queries.

A Data Lake can be extended into a lakehouse by adding reliable table formats, transactions, governance and warehouse-style query performance. Delta Lake, Apache Iceberg and Apache Hudi are common components, but the best choice depends on workloads, cloud services and existing skills.

A strong Data Lake specialist often works with Apache Spark, SQL, Python, Kafka, dbt, orchestration tools and infrastructure automation. Knowledge of IAM, catalogues, data quality, lineage and cloud networking is also important because storage alone does not create a usable platform.

A Data Lake project needs a professional who has operated production pipelines, not only created a proof of concept. The required depth depends on source complexity, governance, latency, migration scope and the number of teams that will consume the data.

A Data Lake engagement can usually be delivered remotely when access, documentation and communication routines are well defined. On-site workshops in Munich may still help with source-system discovery, security reviews and alignment with manufacturing or operations teams.

Look for a Data Lake specialist who can explain design decisions around partitioning, schema evolution, quality checks, lineage, access and cost. Ask how they handled failed pipelines, duplicate data and changing source systems in production, rather than focusing only on tool names.

A useful Data Lake brief describes source systems, expected data types, freshness needs, cloud environment, security constraints and intended consumers. It should also state whether the goal is a migration, a new platform, pipeline improvements, lakehouse capabilities or a governed machine-learning foundation.

The average hourly rate of freelancers in Munich, Germany who have used Data Lake in their recent projects is 103 €, which corresponds to a daily rate of about 825 € based on an 8-hour working day.

Of the freelancers in Munich, Germany who have used Data Lake in their recent projects, 89% hold at least a Bachelor's degree, 63% hold at least a Master's degree, and 11% hold a doctorate.

On average, freelancers in Munich, Germany who have used Data Lake in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 3.4 years.

The most common languages among freelancers in Munich, Germany who have used Data Lake in their recent projects are English (100%), German (90%), and Spanish (30%).

The most common industries among freelancers in Munich, Germany who have used Data Lake in their recent projects are Information Technology (80%), Banking and Finance (60%), and Professional Services (60%).

The most common business areas among freelancers in Munich, Germany who have used Data Lake in their recent projects are Information Technology (95%), Business Intelligence (75%), and Project Management (70%).

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.

Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg

Request a free demo

Get in touch with the FRATCH team and we will get back to you within 4 hours.

Contact form

Would you rather directly get in touch?
We always have the time for a call or email!

FRATCH CEO avatar

Philipp Thomaschewski

FRATCH CEO

LinkedInFRATCH