Data Lake Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Data Lake
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
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).
Hardeep Bhutter
Last position:
Sr. Data Engineer at Charles Schwab Bank
- Designed and implemented end-to-end data pipelines (batch & streaming) using Python, SQL, and Apache Spark, Databricks on AWS reducing ETL latency by 40%.
- Developed serverless event-driven ingestion pipelines using AWS Lambda and SQS, ensuring real-time data availability for downstream analytics.
- Leveraged Google Cloud Platform (GCP) services including BigQuery and Dataflow to manage cross-cloud data warehousing and analytics integration.
- Expertise in DMS (CDC, Full Load) and Airflow for scalable data pipeline automation and orchestration.
- Managed and customized data pipelines using Databricks, Airflow. Automation using Docker, Kubernetes, Terraform.
- Automated data quality checks using dbt to modularize transformations and ensure production-grade data lineage, improving reliability by 30%.
- Collaborated with compliance teams to ensure GDPR and SOC2 alignment. Mentored junior engineers and contributed to architecture refactoring for scalability.
- Created and maintained dashboards in Power BI to provide actionable insights.
Harald Laschitz
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
Alyosh Agarwal
Last position:
Business Intelligence Consultant at Large Private Equity Group
- Business intelligence and KPI specification and playbook for 35 European companies.
Stephan Sahm
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)
Alexandru Gunescu
Last position:
Head of Cloud Infrastructure at BP
- Migrated the Electric Vehicle Charging SaaS App of the EV Division from on-premises and Azure to AWS Cloud, resulting in a hybrid multi-cloud multi-tenant solution
- Developed a streaming data pipeline using AWS MSK for Apache Kafka and implemented an event-driven architecture to ingest and process near real-time data from OCPI-protocol IoT devices
- Implemented multi-tenant strategies including database schema isolation, bridge model for resource sharing, and tenant-based RBAC controls
- Provisioned Kubernetes clusters on AWS EKS with namespaces and RBAC for tenant isolation
- Led migration from on-premises and Azure to AWS using AWS DataSync, Snowball, and Database Migration Service
- Orchestrated collaboration across 5+ systems, vendors, service providers, and on-site teams
- Supported development and maintenance of IT strategy aligned with business requirements
- Managed €40 million infrastructure budget with AWS & Azure cost optimization, achieving 15% savings
- Led 50+ developers to implement advanced database procedures, increasing productivity by 20%
- Spearheaded multi-cloud, multi-tenant infrastructure migration for 30% faster processing times
- Negotiated vendor pricing to reduce payroll/benefits administration costs by 20%
- Developed a two-year infrastructure technology roadmap yielding 25% cost savings
- Tech stack: Kubernetes on AWS EKS, Docker, Kafka/AWS MSK, Terraform, AWS CDK, TypeScript, React, NextJS, Node.js, NestJS, Python, Aurora Serverless, RDS (MySQL, SQL Server), GitHub Actions, Azure DevOps, ArgoCD, AWS Lambda, API Gateway, AWS Security Hub, AWS Database Migration Service, AWS DataSync, AWS Organizations, AWS Control Tower, Odoo, Microsoft Navision, MS Dynamics
Bhanu Avula
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.
Nikolay Tonev
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.
Maziyar Khorrami
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
Velika Ivanova
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.
Natalia Dobrova
Last position:
Senior HR BP for Tech and Marketing at KONUX GmbH
- Org design & HR transformation project.
- OKRs development.
Jonas Anschütz
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
Nandana Roy
Last position:
IT Product Owner at PwC
- Project: SAP migration (ECC to S/4HANA) – US-based internal analytics product to manage finance and personnel performance insights of 10,000+ users across the Americas.
- Led cloud migration from a legacy data warehouse to Azure Data Lake and Databricks, improving system scalability by 40% and reducing manual interventions by 60%.
- Delivered end-to-end product ownership across 3 cross-functional Agile teams using SAFe methodology and Azure DevOps.
- Designed and implemented data pipelines using Azure Data Factory, improving data ingestion speed by 30% and reducing data errors by 25%.
- Defined the product roadmap, backlog, and sprint goals in collaboration with stakeholders, ensuring 95% of deliverables met business expectations.
- Managed the product backlog and prioritised feature development based on stakeholder needs, achieving a 25% increase in sprint velocity and a 100% sprint completion rate.
- Facilitated Agile ceremonies (sprint planning, reviews, retrospectives) that improved team collaboration and reduced delivery times by 20%.
- Led requirement gathering and analysis, enhancing data quality and aligning with business objectives, resulting in a 25% improvement in migration efficiency.
- Worked closely with business owners, achieving a 15% reduction in dispute resolution time and stronger alignment with business value.
- Established KPI dashboards to measure product adoption and platform stability, resulting in 20% improved stakeholder satisfaction.
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)
Position duration
3.3 years (Germany: 2.4 years)
Positions per freelancer
8 (Germany: 10)
Top business areas
Information Technology, Business Intelligence, Project Management
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
89% (Germany: 95%)
Master's degree or higher
61% (Germany: 70%)
Doctorate
6% (Germany: 17%)
Certifications per freelancer
2 (Germany: 4)
Most common languages
English, German, French
Speak two or more languages
95% (Germany: 98%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Munich using Data 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
Core purpose
A data lake stores large amounts of structured, semi-structured, and unstructured data in one place. It is used for analytics, reporting, machine learning, and data sharing across teams. Strong experts know how to keep the lake flexible without turning it into a messy archive.
Common stacks
Data lake work often sits on cloud storage and processing tools.
- Amazon S3, Azure Data Lake Storage, or Google Cloud Storage
- Spark, Databricks, or EMR for processing
- Hive, Trino, or Athena for query access
- Kafka and batch pipelines for ingestion
What good experts do
A strong professional defines folder or table layouts, metadata rules, access control, and lifecycle policies. They also make sure raw data, cleaned data, and analytics-ready data are easy to find. That work matters as much as the storage layer itself.
When companies need help
Freelance support is common when a lake grows too fast, data quality drops, or teams cannot agree on governance. It also helps when a company is moving from a warehouse-only setup to a lake or lakehouse model. In Munich, this often comes up in industry, mobility, finance, and software teams that need shared data access.
Delivery areas
Typical work includes:
- ingestion pipelines and schema handling
- data catalog and lineage setup
- security, permissions, and encryption design
- cost-aware storage and retention rules
- data quality checks and curated zones
What to look for
The best experts write clear data contracts, understand cloud storage limits, and know how to balance openness with control. They can explain trade-offs between a data lake, a warehouse, and a lakehouse. If they cannot describe how users will trust the data, the setup is not finished.
Frequently asked questions
Key details about Data Lake, drawn from the questions we get asked most.
A data lake is used to store raw and processed data in one shared environment for analytics, reporting, and machine learning. It helps teams keep source data, transformed data, and historical data together without forcing one fixed structure too early. Good setups make that data searchable and usable, not just stored.
A data lake keeps data in a more flexible format and usually accepts raw inputs first. A data warehouse is more structured and optimized for fixed reporting patterns. Many companies use both, with the lake feeding the warehouse or supporting broader exploration.
A data lake project often needs outside help when ingestion becomes messy, access rules are unclear, or teams cannot trust what they find. Freelance experts are also useful during cloud migrations, governance redesigns, or when a lakehouse approach is being introduced. The best time to bring in help is before bad structure spreads.
A strong data lake specialist usually also knows cloud storage, SQL, Python, Spark, and data modeling. Knowledge of governance, security, and metadata tools matters too. If the project uses AWS, Azure, or Databricks, that experience is especially useful.
A data lake is the storage foundation; a lakehouse adds table management, reliability, and warehouse-like features on top. In many modern setups, the lakehouse builds on the same storage layer but adds stronger governance and query performance. Companies choose between them based on how much control and structure they need.
Yes, a data lake specialist can often work remotely because most tasks happen in cloud environments and documented pipelines. On-site time can still help at the start of a project, especially for access reviews, stakeholder alignment, or sensitive data discussions. For Munich teams, hybrid collaboration is common when business and technical teams need close contact.
A good data lake professional can explain ingestion, governance, quality, and access control in plain language. Look for concrete examples of how they handled broken schemas, duplicate data, or unclear ownership. Strong answers always connect storage design to how people will actually use the data.
Not exactly. Azure Data Lake usually refers to Microsoft's storage and analytics services for building a data lake, especially Azure Data Lake Storage. The broader term covers the whole design pattern, no matter which cloud or storage system is used.
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 820 € 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, 61% hold at least a Master's degree, and 6% 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 3.3 years.
The most common languages among freelancers in Munich, Germany who have used Data Lake in their recent projects are English (100%), German (89%), and French (32%).
The most common industries among freelancers in Munich, Germany who have used Data Lake in their recent projects are Information Technology (79%), Professional Services (63%), and Banking and Finance (58%).
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 (79%), and Project Management (68%).
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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