Amazon Redshift Expert in Frankfurt
in minutes with vetted, available specialists and precise AI matchingHire experts who design analytical data warehouses, build reliable ELT pipelines and optimize Redshift Spectrum workloads across AWS. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your technical requirements.
Meet FRATCH Experts in Frankfurt, who have recently used Amazon Redshift
Monika T.
Last position:
Senior ETL Lead at Takeda GmbH
- Led design, development, and deployment of data solutions supporting a major pharma acquisition for Takeda Pharmaceutical Company, delivering transparency reporting systems across Azure,Databricks (Python and Shell Scripting) platforms.
- Owned,Designed and developed scalable ELT pipelines to process Customer and Product data using Azure, complex SQL, Databricks, and shell scripting, enabling efficient data integration and processing across multiple sources including job orchestration and workflow automation.
- Implemented performance optimization techniques (query tuning, parallelism, workload optimization), improving system efficiency and processing time.
- Applied strong analytical and problem-solving skills to assess technical solutions and support business requirements for compliance and transparency reporting.
- Designed scalable data foundations suitable for downstream analytics and AI workloads.
- Led data quality initiatives by assessing multiple source data, defining quality metrics, and establishing processes for monitoring and continuous improvement.
Umut G.
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.
Ashkan Z.
Last position:
Microsoft Azure Senior Data Engineer / Senior Data Scientist at Vattenfall Europe
- Advising on the use of analytics and BI tools and services in the Microsoft Azure stack (e.g. MS Fabric, Synapse Workspaces and dedicated SQL pools, SQL Database, PostgreSQL, Snowflake, Databricks, Data Factory, SSIS, Analysis Services, Function Apps, Power BI, ML)
- Independently designing analytics solutions with Python, SQL, etc.
- Designing and implementing ETLs and data pipelines
- Creating and maintaining APIs
- Independently applying CI/CD, testing, and version control
- Data modeling
- Model development and optimization
- Anomaly detection with AI
- Predictive analytics
Used technologies:
- Snowflake
- Fabric
- Azure Synapse Analytics
- Azure DataFactory
- Azure Data Lake
- Azure DevOps
- Databricks
- Spark
- CI/CD
- SQL Database
- Python
- Power Platform
Judith B.
Last position:
BI & Analytics Consulting
- Analysis of web and campaign performance to derive actionable insights for marketing and growth optimization
- Implementation and maintenance of tag management solutions to ensure reliable and consistent data collection
- Continuous development and optimization of reporting structures with a focus on scalability and data quality
- Conducting regular deep-dive analyses and leading monthly stakeholder sessions to present findings and align on optimization measures
- Designing and managing end-to-end data flows from data collection to visualization
- Tools: GA4, Google Tag Manager, Looker Studio, Airbyte, BigQuery
Leonard H.
Last position:
Freelance Software Engineer & Cloud Architect at Leonard HuĂźke - IT Solutions
- Evaluation of potential providers (Snowflake vs Databricks) and design of the analytics data platform using Databricks
- Data storage and ingestion layer with Amazon S3
- Creation of ETL processes and data transformations with AWS Glue and Databricks Notebooks
- Orchestration with AWS Glue Workflow, Databricks Workflow and Databricks DLT
- Processing of unstructured data including text, image and video
- Databricks workspace setup and administration
- Setting up a medallion architecture to ensure data quality
- Evaluation of possible BI tools (Power BI, AWS QuickSight, Tableau)
- Establishing MLOps using MLflow
- Introducing data governance and data lineage using Unity Catalog
Roman K.
Last position:
Senior Data Engineer / Cloud Architect at DB Systel
- Development of a central billing app for cloud costs at DB
- AWS
- Python
- AWS CDK
- RDS
- Spark (PySpark)
- Glue
- Lambda
- CI/CD (GitLab)
- React/Typescript
- data optimization
- Scrum
Ritika S.
Last position:
AWmOpsRtKekEX(CPEliRenIEtN: CInEfoSrs.yDs,aHtaitAarcchhiiEtencetr(gAyW) S)
Global marketing analytics for Hitachi Energy as part of a global data modernization initiative aiming to enhance data retention, historical data availability and provide Eloqua's 2-year retention for remote interaction reporting and analytics.
Analyzed Eloqua's default retention policy and identified risk of data loss for records older than two years.
Designed and implemented historical data preservation strategy by creating transformed tables in the target data platform to archive older data while ensuring data quality dashboards.
Collaborated with the Power BI team to re-point dashboards from raw Eloqua imports to the newly created archival layer.
Leveraged Jira to track and manage data engineering tasks, bugs, and feature requests across Agile sprints; coordinated backlog prioritization and task assignment to align data pipeline development with business needs.
Power BI dashboard optimization:
Worked closely with business stakeholders to assess and understand reporting needs for reverse customer data.
Designed and implemented incremental refresh in Power BI to ensure daily updates without full data reloads.
Collaborated with Azure data engineers to optimize data processing and publication pipelines.
Stakeholder communication & data modeling:
Acted as liaison between Group Data Office and Technology Office to align data modelling standards.
Gathered requirements from data engineering team and participated in weekly status meetings to provide implementation updates and resolve blockers across teams in Germany, Poland, and India.
Documentation & quality assurance:
Prepared end-to-end technical design documentation, data flow diagrams, and Power BI audit guides for future reference.
Participated in UAT sessions with business users to validate data outputs and report accuracy.
Discover over 15,000 top freelancers
Statistics of experts using Amazon Redshift
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 14 years)
Position duration
2.4 years (Germany: 1.9 years)
Positions per freelancer
7 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Information Technology, Advertising, Energy
Certification focus areas
Information Technology, Business Intelligence, Human Resources
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
33% (Germany: 71%)
Doctorate
33% (Germany: 15%)
Certifications per freelancer
5
Most common languages
German, English, Italian
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 Frankfurt 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 Frankfurt using Amazon Redshift
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.
Amazon Redshift 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 (86%)
- Advertising (43%)
- Energy (43%)
- Healthcare (43%)
- Manufacturing (43%)
- Pharmaceutical (43%)
- Professional Services (43%)
- Education (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Redshift does
Amazon Redshift is a fully managed cloud data warehouse for analysing large volumes of structured and semi-structured data. It brings together data from applications, business systems and operational databases so teams can run reporting, dashboards and complex analytical queries in one governed environment.
Core workloads
Redshift supports enterprise analytics, business intelligence and data products that depend on consistent access to historical data. It can serve curated warehouse models, near-real-time reporting and exploratory analysis while integrating with the wider AWS data ecosystem.
- Build dimensional and wide-table warehouse models
- Consolidate data from SaaS, databases and event sources
- Prepare datasets for dashboards, forecasting and machine learning
AWS ecosystem
Strong Redshift work often connects Amazon S3, AWS Glue, Lake Formation, IAM and Amazon CloudWatch. Specialists may also work with Redshift Spectrum for querying data in S3, streaming ingestion, workload management, automated table optimization and SQL-based transformation frameworks such as dbt.
When expertise matters
Companies bring in freelance expertise when a warehouse must be migrated, restructured or made more reliable without slowing business teams down. Specialist support is useful when query costs rise, pipelines fail, permissions become difficult to manage or an existing schema no longer supports reporting needs.
- Migrate workloads from on-premises warehouses or other cloud services
- Improve distribution, sort keys, encoding and workload performance
- Establish monitoring, access controls and recovery procedures
What strong specialists deliver
Experienced professionals connect warehouse design with business requirements. They clarify data ownership, choose suitable ingestion patterns and create models that remain understandable as sources change. They also document decisions, test transformations and leave clear operating guidance for internal teams.
Collaboration in Frankfurt
Redshift projects can be delivered remotely or through on-site collaboration in Frankfurt, depending on security, workshops and team preferences. Local specialists may support German-speaking stakeholders, while many AWS data teams work effectively in English across distributed environments. Quality is shown through sound SQL, maintainable pipelines, measured query improvements and transparent technical decisions.
Frequently asked questions
Before you brief your next project: the most common questions about Amazon Redshift.
Amazon Redshift is used to store and analyse data for reporting, business intelligence, operational analytics and data products. It combines information from sources such as applications, relational databases, SaaS tools and Amazon S3 in a central warehouse.
Amazon Redshift is often considered when a company already relies on AWS services and wants close integration with S3, IAM, Glue and Lake Formation. Snowflake and BigQuery may offer different approaches to workload separation, pricing, governance and multi-cloud use, so the right choice depends on data patterns and existing architecture.
A strong Amazon Redshift specialist usually understands advanced SQL, dimensional modelling, ELT design and warehouse performance tuning. Useful adjacent skills include Amazon S3, AWS Glue, IAM, orchestration tools, dbt, Python, data quality testing and business intelligence tools.
A capable Redshift freelancer should have delivered work similar to the actual assignment, such as a migration, warehouse redesign, pipeline build or performance review. Ask for concrete examples of schema decisions, ingestion handling, access control, monitoring and documentation rather than relying on a technology list alone.
Yes. Amazon Redshift work is well suited to remote collaboration when access, documentation and communication routines are defined clearly. For teams in Frankfurt, a freelancer may work remotely, on site or in a hybrid arrangement, with German or English used according to stakeholder needs.
Review whether the Redshift design is secure, understandable and aligned with query patterns rather than judging it only by dashboard speed. Look for clear data models, tested transformations, sensible distribution and sort choices, reliable monitoring, controlled permissions and evidence that business requirements were understood.
Amazon Redshift may be unsuitable when workloads are dominated by transactional updates, highly variable small queries or requirements that favour a different warehouse architecture. A specialist should first assess data volume, concurrency, latency, ingestion patterns, governance needs and the AWS services already in use.
Before working with Amazon Redshift, the freelancer should clarify source systems, data ownership, refresh expectations, user groups, security boundaries and reporting priorities. They should also confirm whether the assignment covers architecture, pipeline delivery, SQL development, migration, performance tuning or ongoing operations.
The average hourly rate of freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects is 88 €, which corresponds to a daily rate of about 707 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects, 100% hold at least a Bachelor's degree, 33% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects are German (100%), English (100%), and Italian (29%).
The most common industries among freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects are Information Technology (86%), Advertising (43%), and Energy (43%).
The most common business areas among freelancers in Frankfurt, Germany who have used Amazon Redshift in their recent projects are Business Intelligence (100%), Information Technology (100%), and Product Development (57%).
Main locations of FRATCH Experts, who have recently used Amazon Redshift
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 
Munich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
