
Data Lake Experts in Hamburg
matched in minutesHire experts who design scalable data storage, connect ingestion pipelines and make analytics-ready datasets usable across your business. FRATCH matches you quickly with vetted, available freelancers whose skills fit your Data Lake project.
Meet FRATCH Experts in Hamburg, 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).
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
Enrique G.
Last position:
Security Architect at Capgemini
I implemented a Zero-Trust architecture for robust, military-grade maritime container mini data centers based on VMware & Tanzu to support containerized GIS workloads for ground forces. The main focus was on securing communications, workload protection, and data access in contested electronic battle environments affected by jamming, interception, signal manipulation, and constantly changing operational conditions. I designed and architected use cases so that every element of workload, identity, and system could continue to operate independently and securely even in degraded or disrupted scenarios. In parallel, I defined the enterprise and solution security architecture with LeanIX, Bizzdesign, and HOPEX as enterprise architecture, repository, and governance platforms to maintain architecture inventory, relationships, traceability, target pictures, and security governance in complex environments. For the architectural designs, I used Sparx Enterprise Architect to describe formal architecture views, interfaces, trust boundaries, and system architecture in both IT and OT environments. IriusRisk was used for threat modeling of the solution to identify architecture-driven risks, derive security requirements, and detect countermeasures and design gaps directly from the solution models. Risk and compliance management was supported with Archer. Architecture decisions, control gaps, and operational risks were translated into controlled governance and auditable compliance measures. For documentation, collaboration, and visual design, I used Confluence to maintain Architecture Decision Records, Security Blueprints, and workflows. I used Lucidchart and draw.io to create design artifacts tailored to stakeholders. I also defined OT security concepts with support from electrical and mechanical engineers in the areas of oil, vehicle onboard systems, rail, power plants, pharma, gas turbines, and nuclear technology. I created the end-to-end OT security strategy, starting with global policy, developed into standards and procedures, and finally aligned with Bell-LaPadula, Purdue Model, SABSA, TOGAF ADM, CENELEC 50701, IEC 62443, and NIST standards. In addition, I worked with engineering team leads to identify critical KBP assets and place them under protective measures that segmented SCADA, PLC, and HMI assets. I drove collaboration between Security, IT, and OT teams to create standardized workflows and use cases for the OT security solution catalog, while integrating Defense-in-Depth and Zero-Trust principles into operational environments. A key part of my work was integrating multidisciplinary engineering, security, and operations stakeholders into a unified security blueprinting strategy and ensuring that architecture, threat modeling, governance, and documentation were technically strong and operationally practical.
Marcus B.
Last position:
Managing Director at Petermann Brandt GmbH
- Development and implementation of custom IT solutions for key customers.
- More than 15 years of experience in IT and project management, disciplinary leadership of up to 80 employees.
Pouya F.
Last position:
Senior Project Manager at Circle K Deutschland GmbH
- Steering the rebranding of more than 40 applications, over 300 user accounts, and over 150 group mailboxes
- Coordinated with business units, key users, and technical providers for scheduling and implementation
- Analyzed 12 audit findings, developed a transition roadmap, and executed all measures on time
- Defined the new scope according to BSI guidelines
- Supported auditor selection process and prepared status reports for BSI
- Designed a new role model in SAP, aligned with management, and implemented it
- Created and delivered target-group-oriented training for responsible specialists
- Coordinated requirements with network architects, evaluated vendors, and supported contract conclusion
- Managed pre-staging of 300 laptops including configuration management
- Ensured accessibility of critical TotalEnergies applications via VNext / Workspace Access with authentication strategy using Yubikey and Microsoft Authenticator
- Supported go-live while meeting compatibility, security, and availability requirements
- Shifted from a big-bang to an iterative rollout model to reduce risk
- Defined an IT-side on/offboarding process for dual identities (TotalEnergies & Circle K)
- Ensured technical data integrity between Workday, Entra ID, and O365
- Implemented SAP-JDE cost center logic for ServiceNow orders
- Managed the change of company data in over 40 applications, including web portals, templates, and communication
- Led the SEPA mandate changeover for more than 2000 customers
- Oversaw SAP billing logic implementation through an external development team, including testing and go-live validation by 2025-01-01
- Collected IT-related auditor queries, coordinated with internal stakeholders, and prepared response documentation
- Planned and managed migration of 1200 TB of data between two M365 tenants
- Ensured data integrity, access continuity, and minimal downtime across OneDrive, Teams, SharePoint, and mailboxes
- Migrated data lake solutions (AWS & Databricks) in coordination with cloud architects and business units
- Coordinated testing, bug fixes, and go-live in close collaboration with internal teams and external partners
Anurag S.
Last position:
Data Analyst (SME) at Cognizant
- Build data pipelines for raw and curated data layers using AWS S3, Glue, Athena, and Lake Formation
- Establish CI/CD using GitHub Actions or GitLab CI with CodePipeline
- Prototype models into demo APIs packaged with Docker, versioned with Git, added basic tests with pytest, and assist deployments on AWS SageMaker Endpoint
- Perform exploratory data analysis and feature engineering with pandas and PySpark; track experiments in MLflow or Weights and Biases
- Design and execute A/B tests to optimize user engagement and drive data-informed decisions
Daniel P.
Last position:
Professional Development
Attained AWS Certified Cloud Practitioner certification.
Mastered Rust through self-study, including books, online courses, and open-source contributions.
Developed a serverless web application using AWS (RDS, Lambda, Polly, Amplify) and TypeScript/React/D3, managed infrastructure with CDK.
Continuously stayed updated with industry trends through self-education, webinars, and workshops, exploring Data Mesh and FastAPI.
Kai P.
Last position:
Microsoft Azure Synapse and Power BI Developer at Consulting company / International insurance brokerage group
- Built a Microsoft Azure Synapse Data Warehouse solution and developed ETL structures for an international insurance brokerage company
- Created tables, views, and pipelines in Azure Synapse
- Developed Power BI reports for controlling and tax reporting (BAB, IER)
- Technology stack: Microsoft Azure Synapse (Synapse SQL, Synapse Pipelines), Microsoft Power BI (semantic data model, reports), Azure DevOps (Boards, Repos)
- Development languages: DAX, M, SQL
Discover over 15,000 top freelancers
Statistics of experts using Data Lake
Aggregated from the professional profiles of matched freelancers.
Experience
19 years (Germany: 18 years)

Position duration
2.3 years (Germany: 2.4 years)

Positions per freelancer
14 (Germany: 10)

Top business areas
Information Technology, Business Intelligence, Project Management

Top industries
Information Technology, Energy, Banking and Finance

Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
100% (Germany: 95%)
Master's degree or higher
71% (Germany: 70%)
Doctorate
29% (Germany: 18%)

Certifications per freelancer
7 (Germany: 3)

Most common languages
German, English, Spanish

Speak two or more languages
100% (Germany: 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 Hamburg 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 Hamburg 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 (100%)
- Energy (44%)
- Banking and Finance (44%)
- Insurance (33%)
- Professional Services (33%)
- Retail (33%)
- Advertising (22%)
- Transportation (22%)
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 and refined data from many sources in one flexible environment. It can hold structured, semi-structured and unstructured data for reporting, machine learning, operational analysis and long-term exploration. Unlike a traditional warehouse, it does not require every dataset to fit a fixed schema before storage.
Core architecture
A reliable Data Lake combines storage, ingestion, cataloguing, governance and processing. Experts choose patterns such as lakehouse architecture when teams need warehouse-style reliability alongside the flexibility of a lake. They also define zones, metadata standards, access controls, retention rules and data quality checks.
- Object storage such as Amazon S3, Azure Data Lake Storage or Google Cloud Storage
- Processing with Apache Spark, Databricks, Trino or managed cloud services
- Ingestion through Kafka, Fivetran, Airbyte or cloud-native pipeline tools
- Catalogues and governance with Microsoft Purview, AWS Glue or Unity Catalog
Where companies use it
Companies use Data Lakes to bring together application events, customer records, documents, sensor feeds and financial data. In Hamburg, organisations across logistics, manufacturing, aviation, retail and media can use them to connect operational information with analytics and forecasting.
- Centralise data from cloud, on-premises and SaaS systems
- Prepare trusted datasets for business intelligence
- Support machine learning and advanced analytics
- Retain large volumes of historical or semi-structured data
When freelance expertise helps
Freelance specialists are valuable when a company is setting up a new lake, replacing fragmented pipelines or recovering from uncontrolled data growth. They can assess the current estate, choose an architecture, migrate workloads and establish practical governance without slowing delivery. Remote collaboration works well when documentation and ownership are clear; Hamburg-based teams may also need on-site workshops.
Skills that matter
Strong professionals understand both data engineering and the business purpose behind the platform. They work with cloud security, identity and access management, infrastructure as code, orchestration, streaming, SQL and data modelling. They also know how to manage cost, lineage, observability and recovery rather than treating storage as the whole solution.
How to assess quality
Look for specialists who can explain why a Data Lake is appropriate instead of defaulting to it for every workload. Ask for evidence of clear ingestion contracts, discoverable metadata, tested transformations and controls for sensitive data. A good delivery includes documentation, monitoring, ownership and a usable path from raw data to trusted products.
Frequently asked questions
Everything clients usually want to know about Data Lake, in one place.
A Data Lake stores data from many systems in its original or lightly processed form. Companies use it for analytics, machine learning, reporting, event analysis and historical data retention.
A Data Lake accepts a wider range of data formats and usually applies structure when data is read or transformed. A warehouse is typically optimised for governed, structured analytics, while a lake offers more flexibility but needs strong cataloguing and quality controls.
A Data Lake can be extended into a lakehouse by adding transactional reliability, table management and warehouse-style governance. A lakehouse is useful when one environment must support both flexible data exploration and dependable business reporting.
A strong Data Lake specialist usually understands cloud object storage, Apache Spark, SQL, orchestration, streaming and data modelling. Security, identity management, infrastructure as code, observability and data governance are equally important for production work.
The right level depends on the scope, source systems and compliance requirements rather than a fixed number of years. A small ingestion setup may need a focused specialist, while a company-wide Data Lake requires someone who can shape architecture, governance, migration and operational ownership.
Yes, much of a Data Lake project can be delivered remotely through cloud access, shared documentation and structured workshops. On-site sessions in Hamburg can still help with discovery, stakeholder alignment and decisions involving sensitive operational data.
Ask how the Data Lake design handles lineage, access, data quality, failure recovery and cost control. Strong professionals explain trade-offs clearly and can show how raw data becomes discoverable, trusted and useful to its intended consumers.
A Data Lake becomes difficult to use when teams ingest everything without ownership, metadata, quality rules or retention policies. Other common problems include weak access controls, unclear data contracts and pipelines that cannot be monitored or repaired.
The average hourly rate of freelancers in Hamburg, Germany who have used Data Lake in their recent projects is 106 €, which corresponds to a daily rate of about 849 € based on an 8-hour working day.
Of the freelancers in Hamburg, Germany who have used Data Lake in their recent projects, 100% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 29% hold a doctorate.
On average, freelancers in Hamburg, Germany who have used Data Lake in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Hamburg, Germany who have used Data Lake in their recent projects are German (100%), English (100%), and Spanish (11%).
The most common industries among freelancers in Hamburg, Germany who have used Data Lake in their recent projects are Information Technology (100%), Energy (44%), and Banking and Finance (44%).
The most common business areas among freelancers in Hamburg, Germany who have used Data Lake in their recent projects are Information Technology (100%), Business Intelligence (89%), and Project Management (78%).
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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