Amazon Athena Experts in Berlin
in minutes from over 15,000 CVs with the power of AIHire experts who design Athena queries, tune data formats and partitions, and connect S3-based analytics with Glue and Lake Formation. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Amazon Athena
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
Salvation Omorodion
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 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
Gyan Prakash
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 Can
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 Richter
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
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 Amazon Athena
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
2.8 years
Positions per freelancer
8
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%
Master's degree or higher
33%
Doctorate
17%
Certifications per freelancer
3
Most common languages
English, German, Czech
Speak two or more languages
100%
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 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Athena basics
Amazon Athena is a serverless query service for running SQL directly on data in Amazon S3. Companies use it to explore logs, files, and curated datasets without managing query servers. It is often chosen when teams need fast ad hoc analysis over stored data.
Common use cases
- Query event logs and application data in S3
- Build lightweight analytics for reporting
- Inspect data before loading it into a warehouse
- Support compliance, audit, and investigation workflows
Athena fits well for teams that want quick answers from existing files and keep the data in place.
Ecosystem fit
Strong professionals working with Athena usually know AWS Glue, IAM, S3, Lake Formation, and Parquet or JSON data layouts. They also understand how schema design, partitions, and file sizing affect query cost and performance. In Berlin, this skill set is common in data-heavy product teams and analytics groups that work across cloud environments.
When to bring in help
Companies bring in freelance experts when queries are slow, data is messy, or teams need a reliable setup for shared analytics. Help is also useful during migrations from manual reporting, Redshift offloading, or when access rules must be cleaned up. Remote work is often enough, but on-site sessions in Berlin can help align with security and data owners.
What strong experts do
- Write clear SQL for reusable analysis
- Improve partitioning and file formats
- Set up permissions and cross-account access
- Diagnose cost, latency, and data quality issues
A strong Athena specialist knows how to balance query speed, governance, and simple operations. They leave behind readable queries, documented tables, and a setup your team can maintain.
Deliverables
Typical deliverables include query libraries, data catalog setup, access policies, and documentation for analysts or product teams. Some specialists also help define naming rules, folder structures, and refresh routines so Athena stays usable as data grows. The goal is a setup that works for both one-off questions and repeatable reporting.
Frequently asked questions
Questions about Amazon Athena? Start with the answers below.
Amazon Athena is used to run SQL queries on files stored in Amazon S3. Teams use it for log analysis, reporting, audits, and quick exploration of data without running a separate query cluster. It is a good fit when the source data already lives in S3 and the team wants direct access.
Athena is lighter and simpler when you want direct SQL over data in S3. Redshift is usually better for heavier warehouse-style modeling and managed performance tuning, while Spark fits larger transformation workflows and custom processing. A good expert helps choose the right tool for the workload instead of forcing every use case into one system.
A strong Amazon Athena specialist usually knows S3, AWS Glue, IAM, and Lake Formation. Knowledge of Parquet, partitioning, and catalog design matters too, because they affect both performance and access control. SQL quality is important, but the surrounding AWS setup is often what makes the project succeed.
Amazon Athena projects can range from simple query support to complex governance and performance work. A smaller task may only need someone who can clean up SQL and table definitions, while a larger setup benefits from deeper AWS and data modeling knowledge. The more users, sources, and access rules involved, the more important specialist experience becomes.
Athena work is often handled well remotely because most tasks are in SQL, AWS configuration, and data review. On-site time in Berlin can help when the project involves sensitive data, stakeholder workshops, or access approvals. Many teams use a mix: remote delivery with one or two focused in-person sessions.
Ask which data formats they prefer, how they handle partitions, and how they set up permissions. For Amazon Athena, you also want to know how they debug slow queries and whether they document the work for analysts or other specialists. Clear answers should mention the actual tables, data paths, and access model, not just generic AWS talk.
Good Athena work is easy to maintain and easy to explain. Look for clean SQL, sensible table names, documented catalog entries, and a clear approach to file formats and partitioning. If the specialist can show how the setup supports both speed and governance, that is a strong sign.
Yes, Amazon Athena is the official product name, and many people also say AWS Athena or just Athena. In practice, they refer to the same serverless query service for querying data in S3 with SQL. A good freelancer should understand the service under all of these names.
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.
Countries:
Berlin 
Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
