Amazon Athena Experts in Berlin
for fast analytics delivery, matched in minutes from over 15,000 CVs with the power of AIHire experts who query data in Amazon S3, design Athena workgroups and optimize serverless analytics with AWS Glue and Lake Formation. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your project.
Meet FRATCH Experts in Berlin, who have recently used Amazon Athena
Alexander Z.
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 K.
Last position:
Data Expert at Manufacturing
Salvation O.
Last position:
Product Management Consultant at Self-Employed (Freelancer)
- Led end-to-end product discovery and strategy engagements for early-stage founders (pre-seed) clients, defining product vision, OKRs, and go-to-market strategies and roadmaps for their cloud-based and AI-enabled solutions.
- Designed scalable product operating models (Agile/Scrum, backlog governance, KPI frameworks) as part of the partnership, to improve delivery predictability and reduce feature cycle time by up to 30%.
- Built scalable product roadmaps aligned to fundraising milestones, helping founders articulate product vision, product<>market fit, and traction clearly to investors.
Vili D.
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
Gyan P.
Last position:
Senior DevOps and Cloud Architect at Bosch
- Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
- Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
- Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
- Contributed to hiring and technical interviews as part of the recruitment panel.
Recep C.
Last position:
Sr. Software Engineer at Endava
- Designed and deployed scalable REST APIs for enterprise clients
- Led migration of legacy systems to modern maintainable system, reducing deployment time and enabling daily deployments
- Mentored junior developers and collaborated cross-functionally to align technical roadmaps with business goals, improving team velocity by 50%.
- Tech Stack: PHP (Symfony), Golang, PostgreSQL, MySQL, GCP, Terraform, Kubernetes
Christian R.
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Ilya I.
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 Amazon Athena
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 15 years)
Position duration
2.8 years (Germany: 1.9 years)
Positions per freelancer
8 (Germany: 9)
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
83% (Germany: 90%)
Master's degree or higher
33% (Germany: 52%)
Doctorate
17% (Germany: 10%)
Certifications per freelancer
3 (Germany: 4)
Most common languages
English, German, Czech
Speak two or more languages
100%
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 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 Amazon Athena
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 Athena 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 (75%)
- Automotive (50%)
- Professional Services (38%)
- Banking and Finance (25%)
- Media and Entertainment (25%)
- Advertising (13%)
- Aerospace and Defense (13%)
- Education (13%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Serverless analytics
Amazon Athena is a serverless interactive query service from AWS. It runs SQL directly against data stored in Amazon S3, without requiring a database server or cluster to manage. Companies use it for ad hoc analysis, reporting, data exploration and analytics workloads built on a data lake.
Data lake foundations
Athena works with structured and semi-structured data such as Parquet, ORC, JSON and CSV. Strong specialists define tables in the AWS Glue Data Catalog, organize partitions and select formats that keep queries reliable and efficient. They also connect Athena to Lake Formation when access must be governed across teams.
Delivery and tooling
The surrounding ecosystem matters as much as SQL knowledge. Professionals commonly work with:
- AWS Glue crawlers, catalogs and ETL workflows
- Amazon S3 layouts, lifecycle rules and partition schemes
- Lake Formation permissions and data governance
- Amazon QuickSight dashboards and scheduled reports
- CloudTrail, workgroups and query result controls
When expertise matters
Companies bring in freelance expertise when S3 data has grown difficult to query, dashboards return inconsistent results or cloud costs need tighter control. In Berlin, specialists may support local teams on site, remotely or in a hybrid setup, with clear English communication and German helpful where stakeholders require it.
- Migrating warehouse queries to a serverless lake
- Building reliable reporting datasets
- Improving slow or expensive queries
- Setting up permissions and workgroup policies
Quality signals
A strong professional can explain how partition pruning, columnar formats and compression affect Athena performance. They validate schemas, handle evolving data and separate development from production access. Look for practical evidence in query design, data governance, automation and the ability to make findings understandable to analysts and business teams.
Adjacent expertise
Athena projects often include Python, Spark, AWS Lambda or orchestration tools such as Step Functions and Airflow. Experience with Redshift, Snowflake or BigQuery helps when teams compare architectures, but the specialist should still understand Athena’s pay-per-query model and its dependence on well-structured S3 data. Good delivery includes documentation, repeatable deployments and monitoring.
Frequently asked questions
Questions about Amazon Athena? Start with the answers below.
Amazon Athena is used to query data in Amazon S3 with standard SQL. Companies use it for data lake analysis, operational reporting, log investigation, data validation and dashboards connected through services such as Amazon QuickSight.
Amazon Athena queries files in S3 without a warehouse cluster, which suits ad hoc analysis and flexible data lake workloads. Redshift is a dedicated analytical warehouse that can offer more predictable performance for heavily repeated, structured workloads, so the right choice depends on query patterns and data architecture.
A capable AWS Athena specialist should understand S3 data layout, Parquet or ORC, AWS Glue Data Catalog and Lake Formation permissions. Python, ETL design, Amazon QuickSight and infrastructure automation are also valuable when the work extends beyond query writing.
The scope matters more than a fixed career duration. A simple reporting setup may need a specialist who can model S3 data and write dependable queries, while a governed data lake needs deeper experience with Glue, Lake Formation, security, automation and cost-aware performance tuning.
Yes. Amazon Web Services Athena work is well suited to remote collaboration because queries, permissions and infrastructure can be reviewed in shared cloud environments. A Berlin team should agree on working hours, documentation standards and whether German is needed for stakeholder communication.
Ask the professional to explain partitioning, columnar storage, schema evolution and query-result management in the context of your data. Review whether their approach includes reproducible table definitions, controlled permissions, clear documentation and tests for data accuracy rather than focusing only on a working query.
Athena is often a strong fit when source data already lives in Amazon S3 and the team wants serverless SQL without moving it into a separate warehouse. BigQuery and Snowflake may be preferable for different governance, workload, performance or multi-cloud needs, so the decision should follow the data flow and operating model.
An Athena engagement may involve inspecting an S3 lake, correcting Glue schemas, improving partitions, securing workgroups or connecting results to reporting tools. Specialists should expect to work across data formats, AWS permissions and stakeholder requirements, not only write SQL.
The average hourly rate of freelancers in Berlin, Germany who have used Amazon Athena in their recent projects is 92 €, which corresponds to a daily rate of about 732 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Amazon Athena in their recent projects, 83% hold at least a Bachelor's degree, 33% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Amazon Athena in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Berlin, Germany who have used Amazon Athena in their recent projects are English (100%), German (88%), and Czech (13%).
The most common industries among freelancers in Berlin, Germany who have used Amazon Athena in their recent projects are Information Technology (75%), Automotive (50%), and Professional Services (38%).
The most common business areas among freelancers in Berlin, Germany who have used Amazon Athena in their recent projects are Information Technology (100%), Business Intelligence (88%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Amazon Athena
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 
Munich Request a free demo
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