Data Lake Experts in Berlin
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Meet FRATCH Experts in Berlin, who have recently used Data Lake
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.
Jan Krol
Last position:
Data Expert at Manufacturing
Vili Dhamo
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, maintained the product backlog
- Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural
Bertrand Rothen
Last position:
Interim IAM Product Owner (Identity Management) at REWE digital GmbH
- Establishing Identity & Directory Management as a new (split-off) team & product within the IAM cluster.
- Leading the “Identity & Directory Management” product (8 people) as Product Owner.
- Concept for ‘Digital Identities’, i.e. IDs with n users/accounts and strategy for a modernized product offering.
- Upgrading APIs, migrating to a containerized infrastructure, rolling out international markets & standardized solutions across the REWE enterprise group.
- Tech: OpenText™ (NetIQ) eDirectory & Identity Manager, LDAP, SAP HR/HCM, Docker/Kubernetes/Podman, REST APIs, Microsoft Active Directory & Entra ID, postgresDB, Keycloak, Ansible, Cyberark (PAM), Apache Kafka, Jira, Confluence, Miro.
Amogha Sathyanarayana
Last position:
Senior Product Manager - OS, platform, IAM at Aleph Alpha GmbH
- Leading the product lifecycle for sovereign AI platform and operating system teams for enterprise & government clients and internal stakeholders (infra, solution delivery, support, revenue)
- Built and scaled the platform from a 200-user beta to a full rollout of 70K+ members at the Bundesagentur für Arbeit (BA), secured with ISO 42001 and EU AI Act compliance
- Architected the shift to a multi-tenant shared inference, increasing GPU cluster utilization from 20% to 85% and reducing infrastructure cost-to-serve by 40% for SaaS clients
- Shipped model quantization, allowing clients to run advanced LLMs on legacy hardware (A100s GPUs) instead of the H100s, saving upwards of 70% cost per enquiry
- Abstracted complex Helm configurations into a dynamic model manager, reducing the time to install or swap models by ~80%
- Killed an expensive move to build own dashboard service, pivoting to an API-first data strategy that clients can consume directly and saving €100Ks in opex and capex
- Built a safety-first agent marketplace and control plane lighthouse project for a Tier-1 bank, allowing internal teams to deploy autonomous agents within strict regulatory guardrails
Mohamed Ghassen Brahim
Last position:
Lead / Principal Cloud, AI & Security Architect at Freelancer / CC Conceptualise GmbH
Projects:
Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:
- Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
- Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
- Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
- Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
- Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
- Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management
Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:
- Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
- Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
- Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
- Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
- DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
- Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
- Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git
Hai Dang
Last position:
Principal System Architect & Tech Lead at IU International University of Applied Sciences
Leading architecture and delivery of AI-powered educational content platform, managing two development teams with full technical ownership.
Designed and architected the Content Hub platform replacing legacy SiteFusion systems, enabling professors to create AI-assisted learning materials for improved student outcomes.
Established technical strategy, defined architecture requirements, and aligned two cross-functional teams (AI Media Team, TEAQ Team) on a unified delivery roadmap.
Implemented Clean Architecture principles and AI-agent-friendly documentation standards across the engineering organization.
Drove adoption of modern development workflows including CI/CD automation and MongoDB-based content management solutions.
Germo Görtz
Last position:
BI Developer at Rhenus Logistics
- Business intelligence development in the logistics sector.
- Migrating existing reporting and analysis solutions from Cognos to Microsoft BI.
- Using Microsoft SQL Server, SSAS, Power BI, and other Microsoft BI platform components.
Christian Richter
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Viktoria Beran
Last position:
Freelance Global Recruiter IT & Engineering at Freelance Global Recruiter IT & Engineering
- Active sourcing (Europe & Asia)
- End-to-end recruiting (Europe & Asia): coordinating recruitment processes; advising on recruitment strategy
- Collaborating with hiring managers including C-level and Global Vice Presidents
- Preparing contracts and discussing all questions with candidates
- Providing training and mentoring on interview techniques, active sourcing, self-organization, pipeline building
- Many years of comprehensive experience with staffing service providers
- Working with global HR departments including works council
- Very good user skills with MS Office 2011 (Word, PowerPoint, Excel)
- Very good user skills in CRM/ATS systems (Salesforce, Personio, iCIMS, HCL Notes)
Ilya Isakov
Last position:
Data/Platform/Software Engineer/SRE at IT Consulting
- Designed a platform based on IoT, Azure, Kubernetes, and Postgres for an existing application
- Migrated from "click-ops" and UI-defined CI/CD pipelines to infrastructure-as-code with Terraform, enabling complete redeployment of multiple environments
- Technologies: Terraform, OpenTofu, Azure, Azure DevOps, Kafka, IoT, Kubernetes, Grafana, Prometheus, GitOps, relational databases
Discover over 15,000 top freelancers
Statistics of experts using Data Lake
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 18 years)
Position duration
2.3 years (Germany: 2.4 years)
Positions per freelancer
13 (Germany: 10)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Automotive, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
89% (Germany: 95%)
Master's degree or higher
67% (Germany: 70%)
Doctorate
22% (Germany: 17%)
Certifications per freelancer
3 (Germany: 4)
Most common languages
German, English, French
Speak two or more languages
100% (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 Berlin 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 Berlin 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 structured data in one place, ready for analytics, machine learning, and reporting. It often combines object storage, catalog services, and processing tools so teams can keep more source data without forcing a single schema too early.
Common use cases
- Centralize logs, events, files, and warehouse feeds
- Support BI, data science, and ML workflows
- Keep historical data for audit and replay needs
- Build batch and streaming pipelines on one foundation
Core stack
Strong specialists know the surrounding stack, not just the storage layer. That includes Spark, Databricks, Delta Lake, Apache Iceberg, Apache Hudi, Hadoop, Kafka, Airflow, and cloud services such as S3, ADLS, and Google Cloud Storage.
Where projects go wrong
A data lake becomes messy when ingestion rules, metadata, and access control are weak. Companies bring in freelance experts to clean up duplicate data, define zones, improve cataloging, and make the platform usable for analysts and engineers.
What good experts deliver
Good professionals write clear ingestion logic, design partitioning, and set up reliable data quality checks. They also know how to document schemas, manage permissions, and keep pipelines understandable for mixed teams in Berlin and remote setups.
When to hire
Bring in outside help when you need a new lakehouse, a migration from Hadoop or a warehouse-centric setup, or a fix for slow and unreliable pipelines. A strong specialist can also help align platform choices with existing cloud and security standards.
Frequently asked questions
Need clarity? These are the questions we hear most often about Data Lake.
A strong Data Lake is used to store raw and curated data for analytics, reporting, machine learning, and exploration. It helps teams keep source data in one place while still serving different use cases with different processing layers.
A Data Lake keeps data in its original or lightly processed form and is built for flexible access. A warehouse is more structured and query-focused, while a lake often supports broader ingestion, replay, and machine learning work.
No. Data Lake is the broader storage and processing pattern, while Delta Lake is a table and transaction layer that adds reliability features on top of lake storage. Many teams use Delta Lake, Apache Iceberg, or Apache Hudi to make lake data easier to manage.
A good Data Lake specialist usually knows Spark, Kafka, Airflow, and one or more cloud storage services such as S3, ADLS, or Google Cloud Storage. Knowledge of Databricks, Delta Lake, Iceberg, or Hudi is often important when the platform needs table formats and governance.
A Data Lake project benefits from outside expertise when the current setup has unclear ownership, inconsistent data quality, or slow pipelines. It also helps when a company is moving from Hadoop to cloud storage or starting a lakehouse design from scratch.
Yes. Data Lake work is often remote-friendly because most tasks happen in code, cloud consoles, and documentation. Berlin teams may still want on-site time for workshops, security reviews, or stakeholder alignment at the start of the project.
Look for someone who can explain ingestion, cataloging, access control, and data quality in plain terms. A strong Data Lake professional shows clear examples of pipeline design, schema handling, and how they kept data reliable for real users.
A Data Lake expert should also understand data modeling, cloud security, SQL, and orchestration. Depending on the stack, experience with streaming, governance, and cost control can be just as important as the storage layer.
The average hourly rate of freelancers in Berlin, Germany who have used Data Lake in their recent projects is 110 €, which corresponds to a daily rate of about 880 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Data Lake in their recent projects, 89% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 22% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Data Lake in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Berlin, Germany who have used Data Lake in their recent projects are German (100%), English (100%), and French (18%).
The most common industries among freelancers in Berlin, Germany who have used Data Lake in their recent projects are Information Technology (91%), Automotive (55%), and Professional Services (55%).
The most common business areas among freelancers in Berlin, Germany who have used Data Lake in their recent projects are Information Technology (100%), Business Intelligence (64%), 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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