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Big Data Experts

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Hire experts who design data pipelines, tune distributed processing with Spark and Hadoop, and prepare analytics-ready datasets for BI, reporting, and machine learning. Get fast, precise matching with vetted, available freelancers.

Meet FRATCH Experts who have recently used Big Data

Verified expert

Kiriakos Krastillis

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Platform Engineering Tech Lead / Architect

Nickenich
Kiriakos Krastillis

Last position:

Tech Lead / Architect : OTTO API Platform at OTTO

Maturing their API practices on both a business and technology level. My role covers strategy, architecture, developer advocacy as well as hands-on software engineering, enabling both technical teams and business leadership to adopt and act on API-centric principles effectively. Coincidentally, we also establish GitOps, DX and platform best practices with this project.

Highlights:

  • Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
  • Formulating a way forward for API Lifecycle Management at OTTO
  • Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals

API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, React, Node.js, TypeScript, Redocly, reactive programming, CDC, Golang, Gin, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.

Verified expert

Jens Henneberg

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Interim CTO / CDO & Enterprise Architect | AI Compliance & EU AI Act, Azure AI Foundry | Lawyer & Computer Scientist

Wathlingen
Jens Henneberg

Last position:

Interim CTO (occasional assignments) at Fujitsu / FSAS

Stabilizing an Azure/.NET landscape in live operation.

  • Architecture, DevOps, and operational readiness; technical decisions under time pressure
  • Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics

Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps

Verified expert

Sandra Klinkenberg

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Management Consultant, Business Consultant

Burgdorf
Sandra Klinkenberg

Last position:

Webinar Leader - Blackout Prevention and Preparation at SANDRA KLINKENBERG • Management Consultant, self-employed independent business consultant

  • Webinar on Blackout - Brownout - Power failure - how do I recognise it and what can I do?
Verified expert

Martin Hermann

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Senior IT Transformation Consultant | Solution Architect | Cloud Architect | CTO/CIO Advisor

Freilassing
Martin Hermann

Last position:

Lead Product Owner at Energy

  • Team leadership: Prioritization and coordination of four cross-functional teams.
  • Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
  • Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
  • Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
  • Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
  • Organizational development: Improving communication and decision-making structures across all organizational levels.
  • Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
  • Quality assurance: Ensuring high quality standards in processes, services, and deliverables.
Verified expert

Umut Gülac

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Freelancer

Frankfurt
Umut Gülac

Last position:

Data Architect at BA Technology

I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.

I delivered following projects and engagements as a freelancer.

  • Data Migration of CRM System for AL-FA Objekt Service Gmbh
  • Microsoft Software Resales Partnership

I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer

Technical Focus Areas

  • Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
  • DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
  • Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
  • MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
  • Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Verified expert

Patrick Hohensee

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Lead Technical Recruiter | Business Partner AWS EMEA

Berlin
Patrick Hohensee

Last position:

Lead Technical Recruiter | Business Partner AWS EMEA at Amazon Web Services (AWS)

  • Partnered with senior stakeholders across AWS EMEA to drive talent strategy, partner development, and business growth in the cloud ecosystem.
  • Focus areas:
  • Collaboration with Sales & Partner Management on Go-to-Market initiatives
  • Advisory on long-term resource strategy for Cloud, Data, and Security Divisions
  • Supporting internal innovation teams in scaling AI and automation projects
  • Result: Contributed to AWS’s expansion in Central Europe by aligning business, technology, and people strategy.
Verified expert

Gerhard Kolar

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Senior Project Manager and Construction Manager

Wissen
Gerhard Kolar

Last position:

Senior Project Manager and Construction Manager at HENSOLDT Optronics GmbH

  • Building the data center in Oberkochen (defense area)
  • Planning the fiber optic ring, simulation of Wi-Fi coverage
  • Cable routing plan for WAN and LAN cables for office and production (infrastructure)
  • Adaptation of the SAP system (R3) for the Oberkochen site (software)
  • IT transformation of the SAP system to SAP HANA
  • Planning network infrastructure and server technologies in the SAP environment
  • Pré-sales support and setting up change management
  • Independent coordination of utilities according to time, budget and quality
  • Mapping the project in MS Project and SERVICENow
  • Development and design of hardware and software
  • Demand management and portfolio management
  • Building a risk register and migration plan
  • Preparation of payment-supporting documents in coordination with the responsible finance and commercial functions
  • Budget: 5 Mio. - 34 FTE
Verified expert

Halil Oeztoprak

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Principal Cloud & DevSecOps Architect (AWS / Azure / Terraform / Kubernetes / CI-CD)

Bonn
Halil Oeztoprak

Last position:

Senior Cloud Operations & DevSecOps Engineer (Azure / Terraform / CI-CD) at KfW Bankengruppe

  • Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).

  • Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.

  • Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.

  • Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.

  • Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.

  • Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.

  • Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.

  • CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.

  • Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.

  • Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.

  • OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.

  • Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).

  • Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.

  • Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.

  • Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.

  • SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.

  • Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.

  • Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.

  • CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.

  • Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.

  • Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.

Verified expert

Alexander Zhirov

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Senior Data Architect & Data Engineer

Berlin
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.
Verified expert

Philipp Grunert

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Machine Learning & Data Engineer

München
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
Verified expert

Ines Lukin

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Sr UX/UI Designer (B2B, SaaS) Code-First Prototyping

Munich
Ines Lukin

Last position:

UX designer for AI products at freelance

  • Designing AI-first workflows that integrate AI into existing product experiences
  • Developing UX concepts for prompt management, reusable and combined prompt workflows, tagging, search and information organisation
  • Creating user flows, wireframes, prototypes and high-fidelity interfaces in Figma
  • Defining reusable UI patterns, components and interaction logic for scalable products
  • Exploring human-AI interaction patterns with emphasis on user control, transparency and manageable cognitive load
  • Translating product requirements and technical constraints into developer-ready UX/UI specifications
Verified expert

Thomas Meyer

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Executive Consultant, Coach to Management

Weilheim in Oberbayern
Thomas Meyer

Last position:

Executive Consultant, Coach to Management at International consulting firm

  • Support to management on critical strategic topics with high investment volumes (e.g. large project > EUR 250 million).
  • Support for the financing of large projects with a credit volume of EUR 100 million.
  • Advice on difficult personnel issues and on filling leadership positions.
  • Leadership and management in virtual project environments.
  • Strategic consulting on digitalization as well as financing and equity topics.
  • Impulse giver and advisor for stuck negotiations, contract design, and solution options.
Verified expert

Alexander Bromberg

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Senior Data Engineer

Köln
Alexander Bromberg

Last position:

Senior Data Engineer at RWE AG

Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.

Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows

Verified expert

Julian Hillebrand

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Senior IT Project Manager & Program Manager | 12+ years | AI, Cloud, Data, Rollout, Transformation

Solingen
Julian Hillebrand

Last position:

IT Project Manager AI product for automating knowledge-intensive processes at Leading provider of large-scale catering & food services

Project: Concept and implementation of an AI product for four business use cases

Project management of an AI project at a leading provider of large-scale catering and food services, where a production-ready AI product for four use cases was implemented together with an external development partner: automated briefings from CRM and document data, voice-based capture and structuring of reports, detection and merging of duplicates in master data, and data-based market analysis. A central focus was a privacy-compliant architecture that passed the internal IT security review and enabled productive use.

  • Translating business requirements into clearly defined AI use cases with a clear product scope and clear value proposition
  • Selecting and evaluating models and architecture options for text extraction, speech-to-text and context enrichment from business systems, including LLM integration, function calling and retrieval
  • Designing and enforcing an architecture with European hosting, data minimization and masking of personal data as a prerequisite for approval
  • Managing the interfaces between business, IT, IT security and the external development partner under restrictive data access conditions
  • Coordinating with CIO and executive management on data access, risk assessment and approval decisions
  • Preparing the transition into productive use

Discover over 15,000 top freelancers

Statistics of experts using Big Data

Aggregated from the professional profiles of matched freelancers.

Experience

19 years

Position duration

3 years

Positions per freelancer

12

Top business areas

Information Technology, Business Intelligence, Product Development

Top industries

Information Technology, Professional Services, Banking and Finance

Certification focus areas

Information Technology, Project Management, Business Intelligence

Bachelor's degree or higher

92%

Master's degree or higher

64%

Doctorate

17%

Certifications per freelancer

3

Most common languages

German, English, French

Speak two or more languages

98%

Based on our profile pool as of 6 Sep 2026.

Daily rate distribution

0 30 60 90 120
<€400 €400-​800 €800-​1200 €1200-​1600 €1600+

The chart shows how the daily rates of freelancers in this technology 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 using Big Data

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

1000
750
500
250
Rate comparison chart
Daily rate avg. 843 €

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 €

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 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.

About the technology

Big Data basics

Big Data covers the systems and methods used to store, process, and analyze very large, fast, or varied datasets. It is used when classic databases are not enough for scale, speed, or data variety. The goal is simple: turn raw data into reliable output for reporting, products, and decisions.

Common stacks

  • Distributed storage for raw and curated data
  • Batch and stream processing with Spark, Hadoop, and Kafka
  • Data lakes, warehouse layers, and governance controls
  • SQL, Python, Scala, and cloud data services

The exact stack depends on latency, cost, and how many sources must be connected.

What companies build

Big Data experts help build pipelines, event streams, dashboards, recommendation inputs, fraud checks, and customer analytics. They also shape data models, clean noisy sources, and keep records usable for teams that depend on fresh data. Strong work shows up in fewer manual exports and more trust in the numbers.

When freelance help matters

Freelance specialists are often brought in for platform setup, migration work, pipeline rescue, or a short burst of delivery on a hard data task. They are useful when an internal team needs missing Spark, Hadoop, Kafka, or cloud data experience. This is common in finance, retail, logistics, media, and other data-heavy businesses.

What strong experts do

  • Design for scale, failure, and schema change
  • Write clear transformation logic and tests
  • Keep jobs observable and easy to debug
  • Understand data quality, lineage, and access control

Strong professionals do more than move data. They make pipelines dependable, readable, and maintainable.

Working style

Big Data work often starts remotely because the tools, code, and review process live in shared environments. On-site time can help when teams are aligning data domains, security rules, or migration plans. Clear communication matters, especially when business teams and technical specialists need the same definition of a metric.

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Frequently asked questions

Need clarity? These are the questions we hear most often about Big Data.

Big Data is used to collect, store, and process large or fast-moving datasets that standard systems cannot handle well. Companies use it for analytics pipelines, customer insight, fraud detection, reporting, and data products. It is also common when many sources must be combined into one trusted view.

Big Data usually focuses on distributed processing, flexible storage, and handling raw or semi-structured data at scale. A data warehouse is often better for curated reporting and controlled SQL analysis. Many teams use both: Big Data tools for ingestion and transformation, and a warehouse for business-facing queries.

A strong Big Data specialist usually knows Spark, Hadoop, Kafka, SQL, and cloud data services. Depending on the project, that can also include Databricks, Airflow, Flink, Hive, or storage layers such as data lakes. The right mix depends on batch, streaming, or hybrid processing needs.

For Big Data work, look for someone who has shipped pipelines or platforms in environments with real volume, not just toy examples. The best fit depends on the task: migration, streaming, data modeling, governance, or performance tuning. Strong hands-on delivery matters more than broad theory.

Most Big Data tasks can be done remotely because the work happens in code, notebooks, and shared cloud environments. On-site sessions can help at the start of a project, especially for data access, security, and stakeholder alignment. Many companies use a hybrid setup.

Check whether the Big Data specialist can explain data flow, failure handling, and data quality in plain language. Ask for examples of pipeline debugging, performance improvement, and how they keep outputs trustworthy. Good professionals also document assumptions and dependencies clearly.

Big Data affects both technical and business sides. Technical teams build and run the pipelines, while business teams depend on the metrics, dashboards, and data products that come out of them. A good specialist can work with both groups and keep definitions consistent.

A strong Big Data freelancer often brings Python, SQL, cloud knowledge, and an understanding of data modeling. Depending on the project, DevOps habits, testing, and security awareness can matter too. These skills help keep pipelines stable and easier to maintain.

The average hourly rate of freelancers who have used Big Data in their recent projects is 105 €, which corresponds to a daily rate of about 843 € based on an 8-hour working day.

Of the freelancers who have used Big Data in their recent projects, 92% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 17% hold a doctorate.

On average, freelancers who have used Big Data in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 3 years.

The most common languages among freelancers who have used Big Data in their recent projects are German (99%), English (97%), and French (20%).

The most common industries among freelancers who have used Big Data in their recent projects are Information Technology (83%), Professional Services (47%), and Banking and Finance (45%).

The most common business areas among freelancers who have used Big Data in their recent projects are Information Technology (94%), Business Intelligence (75%), and Product Development (74%).

Main locations of FRATCH Experts, who have recently used Big Data

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

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FRATCH CEO

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